DETAILED ACTION
This final Office action is responsive to amendments filed March 3rd, 2026. Claims 1, 4, 6, 9, 11, and 12 have been amended. Claims 1-12 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/26/26 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments, see page 15, filed 03/03/26, with respect to claims 1, 4, 6, 9, 11, and 12 have been fully considered and are persuasive. The claim objections of 12/12/25 has been withdrawn.
Applicant’s arguments, see pages 15-16, filed 03/03/26, with respect to claim 11 have been fully considered and are persuasive. The 35 USC 112(b) rejection of 12/12/25 has been withdrawn.
Applicant's arguments regarding claim rejections under 35 USC 101 filed 03/03/26 have been fully considered but they are not persuasive.
On pages 16-19 of the provided remarks, Applicant argues that the amended claims represent statutory subject matter. Beginning on page 16 of the provided remarks, Applicant argues “the claim sets forth an improvement to the technology of automatic timetable creation that automates and optimizes the process of creating timetables.” Citing paragraphs [0002]-[0008] of the as-filed Specification, Applicant argues that the improvement is a technical solution to a technical problem. Examiner begins by asserting that the identified problem within the as-filed Specification is not technical as the identified “manually collecting and analyzing evidence from questionnaires collected from the passenger, daily work reports of crew members, on-site surveys, etc., points that needs improvement are identified based thereon” is not a technical problem. Per MPEP 2106.05(a), examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality include “Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential).” Therefore, the argued, “automates and optimizes the process of creating timetables” does not present a technical improvement to a technical problem. Applicant’s arguments are not persuasive.
Continuing on pages 17-18 of the provided remarks, Applicant argues “the improvement is also recited in the claims” referencing the claimed “constraint generation process”. Examiner respectfully disagrees and asserts that the constraint generation process as claimed is recited with a high-level of generality such that the argued “computer-implemented specific technical processes under technically relevant conditions” are not present. The specific “process” related steps generating a constraint for with intensity for each timetable variable and creating a new timetable plan based on the generated constraint, which are observations, judgments, and evaluations of the human mind. The claimed “An timetable plan creation system comprising: a storage device; a computing device; the information processing system; A non-transitory computer readable medium storing a timetable plan creation program causing an information processing system to execute a step” are recited so generically (no details whatsoever are provided other than that they are general purpose computing components and regular office supplies) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. Even when viewed in combination, the additional elements in the claims do no more than use the computer components as a tool. There is no change to the computers and other technology that is recited in the claim, and thus the claims do not improve computer functionality or other technology (See PEG 2019). Therefore, the claims fails to integrate the alleged abstract idea into a practical application of the abstract idea demonstrated by a particular improvement to the technology of automatic timetable creation that automates and optimizes the process of creating timetables. The 35 USC 101 rejection is maintained. Applicant’s arguments are not persuasive.
Applicant's arguments regarding claim rejections under 35 USC 103 filed 03/03/26 have been fully considered but they are not persuasive.
On pages 19-22 of the provided remarks, Applicant argues that the cited prior art does not disclose the amended claim limitations. Beginning on page 21 of the provided remarks, Applicant argues “Fournier does not disclose a plurality of plan creation algorithms composed on a plurality of optimization models having an execution order, as set forth in claim 1.” Examiner respectfully disagrees and begins by citing paragraph [0047] of the as-filed Specification, “the plan-creation-algorithm information 118 is a collection of records each of which includes an algorithm ID that uniquely indicates each algorithm as the unique identifier, and the following pieces of information: the number in an execution order of procedures in the algorithm; a timetable variable to be processed in that number of the execution order (changing timetable variable)”. Under broadest reasonable interpretation, the execution of the argued “a plurality of plan creation algorithms composed on a plurality of optimization models having an execution order” merely represents the optimization of a timetable variable being output by a model. Per cited paragraph [0032] of Fournier, “The system can include a model generator 210 that creates energy model(s) that can be collected by the data collector and further utilized by the modify component (not shown).” This discloses the claimed plurality of optimization models, which in combination with cited Doner discloses the amended claim limitations. Applicant’s arguments are not persuasive.
Continuing on page 22 of the provided remarks, Applicant argues “Doner also does not disclose “a plan creation process for creating a new timetable plan by executing each of the plan creation algorithms that have been selected in the algorithm selection process, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process to each of the plan creation algorithms,” as set forth in claim 1.” Examiner respectfully disagrees and asserts that while Applicant has cited paragraph [0031] as an argument for why Doner does not disclose the amended claim limitations, Applicant has failed to acknowledge the cited paragraphs (including [0055], “the yard performance model calculating the initial task flow rates based on an initial state of train schedules”) regarding the creation of a new timetable. Per claim 4, the execution of the railyard performance algorithm computes the task flow rates and subsequence claim 5 discloses the step of calculating a train schedule based on the computed task flow rates. Therefore, the cited prior art discloses the amended claim limitations. The 35 USC 103 rejection is maintained. Applicant’s arguments are not persuasive.
Claim Objections
Claims 1, 6, and 11 are objected to because of the following informalities:
the limitation beginning “third information” recites “associating a timetable variable” which is a typographical error that should recite “associating the plurality of timetable variables”;
the limitation beginning “an algorithm selection process” recites “the plan creation algorithm” which is a typographical error that should recite “the plan creation algorithms”;
Appropriate correction is required.
Claim 12 is objected to because of the following informalities:
the limitation beginning “third information” recites “associating a timetable variable” which is a typographical error that should recite “associating the plurality of timetable variables”;
the limitation beginning “a plan creation process” recites “the plan creation has algorithms that have” which is a typographical error that should recite “the plan creation algorithms that have”;
the limitation beginning “a plan creation process” ends reciting “the plan creation algorithm” which is a typographical error that should recite “the plan creation algorithms”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter;
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself.
Claims 1-11
Step 1: Independent claims 1 (system), 6 (method), 11 (non-transitory computer-readable medium) and dependent claims 2-5, and 7-10, respectively, fall within at least one of the four statutory categories of 35 U.S.C. 101: (i) process; (ii) machine; (iii) manufacture; or (iv) composition of matter. Claim 1 is directed to a system (i.e. machine); claim 6 is directed to a method (i.e. process); and claim 11 is directed to a non-transitory computer-readable medium (i.e. manufacture).
Step 2A Prong 1: The independent claims recite timetable plan creation method, comprising: causing an information processing system to have a storage device that stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute a timetable plan of a transport service, second information that contains information of a plurality of plan creation algorithms for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables being updated by the plan creation algorithms, and the evaluation index is to be improved by executing the creation algorithm, and fourth information that contains information on a desired change of the intensity of the constraint of the first information; and causing the information processing system to execute: a constraint generation process for generating a constraint with an intensity, based on the first information and the fourth information, the constraint being one generated for each of the timetable variables of a to-be-created timetable plan, an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information, the plan creation algorithms are for improving a quality of the to-be-created timetable plan; and a plan creation process for creating a new timetable plan by executing each of the plan creation algorithms that have been selected in the algorithm selection process, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process to each of the plan creation algorithms (Certain Method of Organizing Human Activity & Mental Process), which are considered to be abstract ideas (See PEG 2019 and MPEP 2106.05). [Examiner notes the underlined limitations above recite the abstract idea].
The steps/functions disclosed above and in the independent claims recite the abstract idea of Certain Methods of Organizing Human Activity because the claimed limitations are creating a new timetable plan of a transport service, which is managing relationships and interactions. The Applicant’s claimed limitations are creating a new timetable plan of a transport service, which recite the abstract idea of Organizing Human Activity.
The steps/functions disclosed above and in the independent claims recite the abstract idea of Mental Process because the claimed limitations are generating a constraint for with intensity for each of the timetable variables and creating a new timetable plan based on the generated constraint, which are observations, judgments, and evaluations of the human mind. The Applicant’s claimed limitations are generating a constraint for with intensity for each of the timetable variables and creating a new timetable plan based on the generated constraint, which recite the abstract idea of Mental Process.
In addition, dependent claims 2-5 and 7-10 further narrow the abstract idea and recite further defining the specification of a condition that matches the intensity and constraint indicated in the first information; reflecting a desired change of the intensity based on if the change restriction constraint matches with fourth information; calculating a relative distance of the aim value to the evaluation index; setting a score for the plan creation algorithm; selecting the plan creation algorithm; executing the plan creation algorithm within a certain range. These processes are similar to the abstract idea noted in the independent claims because they further the limitations of the independent claims which recite a certain method of organizing human activity which include managing interactions as well as mental processes. Accordingly, these claim elements do not serve to confer subject matter eligibility to the claims since they recite abstract ideas.
Step 2A Prong 2: In this application, the above “stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute a timetable plan of a transport service, second information that contains information of a plurality of plan creation algorithms for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables being updated by the plan creation algorithms, and the evaluation index is to be improved by executing the creation algorithm, and fourth information that contains information on a desired change of the intensity of the constraint of the first information” steps/functions of the independent claims would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because receiving/storing data and displaying data merely add insignificant extra-solution activity and merely adds the words to apply it with the judicial exception. Also, the claimed “An timetable plan creation system comprising: a storage device; a computing device; the information processing system; A non-transitory computer readable medium storing a timetable plan creation program causing an information processing system to execute a step” would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because the claimed structure merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See PEG 2019 and MPEP 2106.05).
In addition, dependent claims 2-5 and 7-10 further narrow the abstract idea and dependent claims 2, 4, 5, 7, 9, and 10 additionally recite “acquires information of the to-be- created timetable plan and of a creation date of the to-be- created timetable plan”; “acquires information regarding a status of a mobile resource in the transport service and up to an execution date of the timetable plan”; “acquires the to-be-created timetable plan and a current value of an evaluation index of the to-be- created timetable plan”; “acquires an aim value relating to the evaluation index and a changeable variable”; “acquires the to-be-created timetable plan and an update range”; “acquires a change restriction constraint of the to-be-created timetable plan”; “acquires a plan creation algorithm selected in the algorithm selection process”; and “stores the obtained timetable plan as a result timetable plan” which do not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because receiving/storing data and displaying data merely add insignificant extra-solution activity and the claimed “computing device” and “information processing system” which do not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because the claimed structure merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See PEG 2019 and MPEP 2106.05).
The claimed “An timetable plan creation system comprising: a storage device; a computing device; the information processing system; A non-transitory computer readable medium storing a timetable plan creation program causing an information processing system to execute a step” are recited so generically (no details whatsoever are provided other than that they are general purpose computing components and regular office supplies) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. Even when viewed in combination, the additional elements in the claims do no more than use the computer components as a tool. There is no change to the computers and other technology that is recited in the claim, and thus the claims do not improve computer functionality or other technology (See PEG 2019).
Step 2B: When analyzing the additional element(s) and/or combination of elements in the claim(s) other than the abstract idea per se the claim limitations amount(s) to no more than: a general link of the use of an abstract idea to a particular technological environment and merely amounts to the application or instructions to apply the abstract idea on a computer (See MPEP 2106.05 and PEG 2019). Further, method claims 6-10; system claims 1-5; and a non-transitory computer-readable medium claim 11 recite “An timetable plan creation system comprising: a storage device; a computing device; the information processing system; A non-transitory computer readable medium storing a timetable plan creation program causing an information processing system to execute a step”; however, these elements merely facilitate the claimed functions at a high level of generality and they perform conventional functions and are considered to be general purpose computer components which is supported by Applicant’s specification in Paragraphs 0026-0032 and Figures 1-2. The Applicant’s claimed additional elements are mere instructions to implement the abstract idea on a general purpose computer and generally link of the use of an abstract idea to a particular technological environment. Also, the above “stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute a timetable plan of a transport service, second information that contains information of a plurality of plan creation algorithms for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables being updated by the plan creation algorithms, and the evaluation index is to be improved by executing the creation algorithm, and fourth information that contains information on a desired change of the intensity of the constraint of the first information” steps/functions of the independent claims would not account for significantly more than the abstract idea because receiving data and displaying/presenting data (See MPEP 2106.05) have been identified as well-known, routine, and conventional steps/functions to one of ordinary skill in the art. When viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
In addition, claims 2-5 and 7-10 further narrow the abstract idea identified in the independent claims. The Examiner notes that the dependent claims merely further define the data being analyzed and how the data is being analyzed. Similarly, claims 2, 4, 5, 7, 9, and 10 additionally recite “acquires information of the to-be- created timetable plan and of a creation date of the to-be- created timetable plan”; “acquires information regarding a status of a mobile resource in the transport service and up to an execution date of the timetable plan”; “acquires the to-be-created timetable plan and a current value of an evaluation index of the to-be- created timetable plan”; “acquires an aim value relating to the evaluation index and a changeable variable”; “acquires the to-be-created timetable plan and an update range”; “acquires a change restriction constraint of the to-be-created timetable plan”; “acquires a plan creation algorithm selected in the algorithm selection process”; and “stores the obtained timetable plan as a result timetable plan” which do not account for additional elements that amount to significantly more than the abstract idea because receiving data and displaying/presenting data (See MPEP 2106.05) have been identified as well-known, routine, and conventional steps/functions to one of ordinary skill in the art and the claimed “computing device” and “information processing system” which do not account for additional elements that amount to significantly more than the abstract idea because the claimed structure merely amounts to the application or instructions to apply the abstract idea on a computer and does not move beyond a general link of the use of an abstract idea to a particular technological environment (See MPEP 2106.05). The additional limitations of the independent and dependent claim(s) when considered individually and as an ordered combination do not amount to significantly more than the abstract idea. The examiner has considered the dependent claims in a full analysis including the additional limitations individually and in combination as analyzed in the independent claim(s). Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim 12
Step 1: Independent claim 12 (system), respectively, falls within at least one of the four statutory categories of 35 U.S.C. 101: (i) process; (ii) machine; (iii) manufacture; or (iv) composition of matter. Claim 12 is directed to a system (i.e. machine).
Step 2A Prong 1: The independent claim recites A transportation plan system comprising: a timetable plan creation system including a storage device that stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute an timetable plan of a transport service, second information that contains a creation algorithm for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables be updated by the plan creation algorithms, and the evaluation index being one to be improved by executing the plan creation algorithms, and fourth information that contains information on a desired change of the intensity of the constraint of the first information, and a computing device that executes a constraint generation process for generating a constraint with an intensity, based on the first information and the fourth information, the constraint being one generated for each of the timetable variables of a to-be-created timetable plan, an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information, the plan creation algorithms being one for improving a quality of the to-be-created timetable plan and each plan creation algorithms are composed of a plurality of optimization models having an execution order, and a plan creation process for creating a new timetable plan by executing each of the plan creation has algorithms that have been selected in the algorithm selection process, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process being applied to each of the plan creation algorithm; a traffic control system configured to: acquire the timetable plan from the timetable plan creation system, and control an operation of a mobile resource in the transport service, based on the timetable plan; and a resource management system configured to: acquire the timetable plan and the fourth information from the timetable plan creation system, and perform management of the mobile resource in the transport service, based on the timetable plan and the fourth information (Certain Method of Organizing Human Activity & Mental Process), which are considered to be abstract ideas (See PEG 2019 and MPEP 2106.05). [Examiner notes the underlined limitations above recite the abstract idea].
The steps/functions disclosed above and in the independent claims recite the abstract idea of Certain Methods of Organizing Human Activity because the claimed limitations are creating a new timetable plan of a transport service; controlling an operation of a mobile resource in the transport service based on the timetable plan; and performing management of the mobile resources in the transport service, which is managing relationships and interactions. The Applicant’s claimed limitations are creating a new timetable plan of a transport service; controlling an operation of a mobile resource in the transport service based on the timetable plan; and performing management of the mobile resources in the transport service, which recite the abstract idea of Organizing Human Activity.
The steps/functions disclosed above and in the independent claims recite the abstract idea of Mental Process because the claimed limitations are generating a constraint for with intensity for each of the timetable variables; creating a new timetable plan based on the generated constraint; controlling an operation of a mobile resource in the transport service based on the timetable plan; and performing management of the mobile resources in the transport service, which are observations, judgments, and evaluations of the human mind. The Applicant’s claimed limitations are generating a constraint for with intensity for each of the timetable variables; creating a new timetable plan based on the generated constraint; controlling an operation of a mobile resource in the transport service based on the timetable plan; and performing management of the mobile resources in the transport service, which recite the abstract idea of Mental Process.
Step 2A Prong 2: In this application, the above “stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute an timetable plan of a transport service, second information that contains a creation algorithm for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables be updated by the plan creation algorithms, and the evaluation index being one to be improved by executing the plan creation algorithms, and fourth information that contains information on a desired change of the intensity of the constraint of the first information”; “acquire the timetable plan from the timetable plan creation system”; and “acquire the timetable plan and the fourth information from the timetable plan creation system” steps/functions of the independent claims would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because receiving/storing data and displaying data merely add insignificant extra-solution activity and merely adds the words to apply it with the judicial exception. Also, the claimed “A transportation plan system comprising: a timetable plan creation system including a storage device; a computing device; a traffic control system; a resource management system” would not account for additional elements that integrate the judicial exception (e.g. abstract idea) into a practical application because the claimed structure merely adds the words to apply it with the judicial exception and mere instructions to implement an abstract idea on a computer (See PEG 2019 and MPEP 2106.05).
The claimed “A transportation plan system comprising: a timetable plan creation system including a storage device; a computing device; a traffic control system; a resource management system” are recited so generically (no details whatsoever are provided other than that they are general purpose computing components and regular office supplies) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. Even when viewed in combination, the additional elements in the claims do no more than use the computer components as a tool. There is no change to the computers and other technology that is recited in the claim, and thus the claims do not improve computer functionality or other technology (See PEG 2019).
Step 2B: When analyzing the additional element(s) and/or combination of elements in the claim(s) other than the abstract idea per se the claim limitations amount(s) to no more than: a general link of the use of an abstract idea to a particular technological environment and merely amounts to the application or instructions to apply the abstract idea on a computer (See MPEP 2106.05 and PEG 2019). Further, system claim 12 recites “A transportation plan system comprising: a timetable plan creation system including a storage device; a computing device; a traffic control system; a resource management system”; however, these elements merely facilitate the claimed functions at a high level of generality and they perform conventional functions and are considered to be general purpose computer components which is supported by Applicant’s specification in Paragraphs 0026-0032 and Figures 1-2. The Applicant’s claimed additional elements are mere instructions to implement the abstract idea on a general purpose computer and generally link of the use of an abstract idea to a particular technological environment. Also, the above “stores first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute an timetable plan of a transport service, second information that contains a creation algorithm for creating the timetable plan, third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables be updated by the plan creation algorithms, and the evaluation index being one to be improved by executing the plan creation algorithms, and fourth information that contains information on a desired change of the intensity of the constraint of the first information”; “acquire the timetable plan from the timetable plan creation system”; and “acquire the timetable plan and the fourth information from the timetable plan creation system” steps/functions of the independent claims would not account for significantly more than the abstract idea because receiving data and displaying/presenting data (See MPEP 2106.05) have been identified as well-known, routine, and conventional steps/functions to one of ordinary skill in the art. When viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself.
The additional limitations of the independent claim(s) when considered individually and as an ordered combination do not amount to significantly more than the abstract idea. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-3, 5-8, and 10-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fournier (U.S 2014/0012454 A1) in view of Doner (US 2002/0082814 A1).
Claim 1, 6 and 11
Regarding Claim 1, Fournier discloses the following:
A timetable plan creation system comprising [see at least Paragraph 0031 for reference to the system can create a timetable for two or more vehicles as well as optimize an existing timetable for two or more disparate vehicles; Figure 1 and related text regarding the system for optimizing energy consumption by synchronizing a first vehicle and a second vehicle; Figure 3 and related text regarding the system for controlling two or more vehicles based upon an optimized timetable that conserves energy by synchronizing a first vehicle and a second vehicle; Figure 4 and related text regarding a system for creating an optimized timetable offline and employing such optimized timetable online to conserve energy by synchronizing a first vehicle and a second vehicle]
a storage device that stores: first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute a timetable plan of a transport service [see at least Paragraph 0027 for reference to the data collector aggregating static and/or dynamic input; Paragraph 0030 for reference to the data collector aggregating information related to the timetable, a static input, and/or dynamic input; Paragraph 0030 for reference to static input including a Quality of Service (QoS) constraint, a constraint, an energy model, a tolerance, an energy profile, a network topology, an electric efficiency, an origin/destination matrix, a portion of a timetable, an energy transportation, a loss of energy, among others; Paragraph 0031 for reference to a timetable being created which takes into account at least one of a security constraint, a quality of service constraint, the issue of energy consumption, and the like; Paragraph 0042 for reference to tables being created to maximize quality of service, security and other constraints; Figures 1, 2, and 4 and related text regarding item 120 ‘data collector’]
second information that contains information of a plurality of plan creation algorithms for creating the timetable plan [see at least Paragraph 0027 for reference to the system including a modify component that optimizes the timetable based upon the aggregated information; Paragraph 0028 for reference to the system being computer-implemented via software such that the modify component adjusts a timetable to create the optimized timetable; Figure 1 and related text regarding item 130 ‘modify component’; Figure 4 and related text regarding item 430 ‘modify component’]
third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables being updated by the plan creation algorithms, and the evaluation index is to be improved by executing the plan creation algorithms [see at least Paragraph 0037 for reference to the monitor tracking the vehicles in comparison with at least one of the optimized timetable and/or measured amount of energy; Paragraph 0266 for reference to the method including tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy]
fourth information that contains information on a desired change of the intensity of the constraint of the first information [see at least Paragraph 0037 for reference to the trigger including threshold values that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy, monitoring a threshold value related to the measured amount of energy]
a computing device that executes: a constraint generation process for generating a constraint with an intensity, based on the first information and the fourth information, the constraint being one generated for each of the timetable variables of a to-be-created timetable plan [see at least Paragraph 0028 for reference to the system being computer-implemented via software such that the modify component adjusts a timetable to create the optimized timetable; Paragraph 0031 for reference to a timetable being created which takes into account at least one of a security constraint, a quality of service constraint, the issue of energy consumption, and the like; Paragraph 0042 for reference to tables being created to maximize quality of service, security and other constraints; Figure 1 and related text regarding item 130 ‘modify component’; Figure 4 and related text regarding item 430 ‘modify component’]
based on the third information, the plan creation algorithm being for improving a quality of the to-be-created timetable plan and each plan creation algorithms are composed of a plurality of optimization models [see at least Paragraph 0027 for reference to the modify component generating an optimized timetable wherein the optimized timetable improves energy consumption; Paragraph 0032 for reference to the system can include a model generator that creates energy model(s) that can be collected by the data collector and further utilized by the modify component; Paragraph 0040 for reference to a genetic algorithm being used to minimize an objective function – corresponding to the global energy consumption over a time horizon – computed with a liner program; Paragraph 0101-0102 for reference to the algorithmic approaches to model energy flows in the railway network wherein different formulations can be inferred regarding the topology of the real system one wants to model and to the simplifications one has to make to be able to optimize the model in reasonable time; Paragraph 0180 for reference to genetic algorithms (GAs) including instantiate a population of timetables slightly different from the initial one, classify the timetables, mate them (e.g., crossover), mutate them, and go back to instantiating a population of timetables until termination criterion]
a plan creation process for creating a new timetable plan by executing each of the plan creation algorithms, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process being applied to each of the plan creation algorithms [see at least Paragraph 0027 for reference to system further includes a modify component that optimizes the time table based upon the aggregated information and adjusts (e.g., modifies) at least one of a dwell time for a vehicle located within a terminal, a departure time for a vehicle located within a terminal, and/or speed profile for a vehicle for a terminal; Paragraph 0033 for reference to the models being utilized to create and energy model for an environment in which two or more trains are to be synchronized with an optimized timetable; Paragraph 0037 for reference to the trigger including threshold values or triggers that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to the method updating the modified timetable based upon the threshold value or the tracking of the vehicles]
While Fournier discloses the limitations above, it does not disclose an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information and each plan creation algorithms are composed of a plurality of optimization models having an execution order.
However, Doner discloses the following:
A timetable plan creation system comprising [see at least Paragraph 0022 for reference to a system for implementing a yard performance model; Figure 1 and related text regarding a system used to implement the railyard performance model]
a storage device that stores: first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each plurality of timetable variables that constitute a timetable plan of a transport service [see at least Paragraph 0022 for reference to the system including a computer which includes a processor for executing all functions of computer and a memory storage device for storing data and algorithms and a databased for storing specific additional data; Paragraph 0022 for reference to inputs including queries, parameters, and data related to yard performance; Paragraph 0022 for reference to in response to yard master’s inputs, computer utilizes memory and databased to solve equations and execute algorithms implemented in the yard performance model; Paragraph 0038 for reference to the yard parameter, input schedule and output schedule can be saved within system for later reuse; Figure 1 and related text regarding item 30 ‘memory storage device’ and item 34 ‘database’]
third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan [see at least Paragraph 0039 for reference to yard topology parameters being based on the capacity of the subyards in terms of railcars wherein the initial levels of cars in each yard are determined before any simulation begins based on those cars in the receive and departure yard; Paragraph 0046 for reference to schedule parameters defining a train schedule and including the number of trains the schedule will contain, the total time interval for the schedule, whether or not inbound train arrival times will be perturbed normally about their nominal values, a number assigned as a train ID, the number of cars in the train, the expected arrival time of the train, offset from the beginning of the simulation interval, and a standard deviation about inbound train arrival time, which will be used with a normal distribution to vary train arrival times about their specified arrival times when the variable input schedule mode is chosen]
an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information, the plan creation algorithm being for improving a quality of the to-be-created timetable plan and each plan creation algorithms are composed of a plurality of optimization models having an execution order [see at least Paragraph 0006 for reference to the method of allocating the available resources and services within the railyard in a given time period to optimize the flow of a collection of trains; Paragraph 0022 for reference to In response to the yard master’s inputs, computer utilizes processor, memory, and database to solve equations and execute algorithms implemented in the yard performance model; Paragraph 0038 for reference to the selection of an algorithm being static, dynamic headend first or backlog first based on the task load and labor movements during the simulation; Paragraph 0055 for reference to the yard performance model being best described by partitioning the performance model into submodels; Examiner noting that the “static, dynamic headend first, or backlog first” being analogous to the claimed “execution order”]
a plan creation process for creating a new timetable plan by executing each of the plan creation algorithms that have been selected in the algorithm selection process, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process to each of the plan creation algorithms [see at least Paragraph 0055 for reference to the yard performance model calculating the initial task flow rates based on an initial state of train schedules; Paragraph 0137 beginning “A method in accordance with Claim 4 wherein said step of determining” for reference to the determination of a train schedule including calculating a train schedule based on the computed task flow rates; Paragraph 0137 beginning “A system for managing railcar movement in a railyard” for reference to determining if a train schedule can be met based on the simulated yard task flow; Claim 4 and related text regarding the railyard performance algorithm comprising the steps of computing task flow rates based on the updated task backlogs; Claim 5 and related text regarding the calculating a train schedule based on the computed task flow rates]
Before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify the timetable method of Fournier to include the algorithm selection of Doner. Doing so would assist in expediting and simplifying the process of moving railcars through a railyard from arrival to departure, as stated by Doner (Paragraph 0002).
Regarding claims 6 and 11, the claims recite limitations already addressed by the rejection of claim 1. Regarding claim 6, Fournier teaches a timetable plan creation method [Paragraph 0023, 0040, & Figure 8]. Regarding claim 11, Fournier teaches a non-transitory computer-readable medium storing a timetable plan creation program causing an information processing system to execute a step [Paragraph 0028 & 0058]. Therefore, claims 6 and 11 are rejected as being unpatentable in view of Fournier and Doner.
Claims 2 and 7
While the combination of Fournier and Doner disclose the limitations above, regarding Claim 2, Fournier discloses the following:
wherein in the constraint generation process, the computing device acquires information of the to-be- created timetable plan and of a creation date of the to-be- created timetable plan [see at least Paragraph 0030 for reference to static input including a Quality of Service (QoS) constraint, a constraint, an energy model, a tolerance, an energy profile, a network topology, an electric efficiency, an origin/destination matrix, a portion of a timetable, an energy transportation, a loss of energy, among others; Paragraph 0031 for reference to a timetable being created which takes into account at least one of a security constraint, a quality of service constraint, the issue of energy consumption, and the like; Paragraph 0042 for reference to tables being created to maximize quality of service, security and other constraints]
the computing device acquires information regarding a status of a mobile resource in the transport service and up to an execution date of the timetable plan [see at least Paragraph 0037 for reference to the monitor tracking the vehicles in comparison with at least one of the optimized timetable and/or measured amount of energy; Paragraph 0266 for reference to the method including tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy]
the computing device specifies a condition that matches with the intensity and with the constraint indicated in the first information, by using the acquired timetable plan, the acquired creation date, and the information regarding the status of the mobile resource [see at least Paragraph 0037 for reference to the trigger including threshold values that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy, monitoring a threshold value related to the measured amount of energy]
the computing device stores, in the storage device, the condition as a change restriction constraint that serves as the first information regarding the timetable plan [see at least Paragraph 0027 for reference to the data collector aggregating static and/or dynamic input; Paragraph 0030 for reference to the data collector aggregating information related to the timetable, a static input, and/or dynamic input; Paragraph 0037 for reference to trigger can include threshold values or triggers that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Figures 1, 2, and 4 and related text regarding item 120 ‘data collector’ & item 420 ‘trigger’]
Regarding claim 7, the claim recites limitations already addressed by the rejection of claim 2.
Claims 3 and 8
While the combination of Fournier and Doner disclose the limitations above, regarding Claim 3, Fournier discloses the following:
wherein if the change restriction constraint that matches with the fourth information is present, the computing device further executes a process for reflecting a desired change of the intensity included in the fourth information, to the change restriction constraint [see at least Paragraph 0037 for reference to trigger can include threshold values or triggers that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0184 for reference to online optimization including criteria to trigger the optimization; Figure 4 and related text regarding item 420 ‘trigger’]
Regarding claim 8, the claim recites limitations already addressed by the rejection of claim 3.
Claims 5 and 10
While the combination of Fournier and Doner disclose the limitations above, regarding Claim 5, Fournier discloses the following:
wherein in the plan creation process, the computing device acquires the to-be-created timetable plan and an update range [see at least Paragraph 0070 for reference to optimization being a modification of several parameters of an initial timetable which minimizes the energy consumption; Paragraph 0071 for reference to the optimization needs the information about stabling/unstabling trains at terminals as well as rolling stock types, speed profiles associated to every trip
the computing device acquires a change restriction constraint of the to-be-created timetable plan [see at least Paragraph 0063 for reference to the system including a graphic user interface (GUI) that allows setting parameters of optimization in real time; Paragraph 0064 for reference to optimization would indeed be done modifying the dwell times and departures at terminals and/or speed profiles]
the computing device acquires a plan creation algorithm selected in the algorithm selection process [see at least Paragraph 0027 for reference to the modify component generating an optimized timetable wherein the optimized timetable improves energy consumption; Paragraph 0040 for reference to a genetic algorithm being used to minimize an objective function – corresponding to the global energy consumption over a time horizon – computed with a liner program; Paragraph 0101-0102 for reference to the algorithmic approaches to model energy flows in the railway network wherein different formulations can be inferred regarding the topology of the real system one wants to model and to the simplifications one has to make to be able to optimize the model in reasonable time]
the computing device executes the plan creation algorithm for the timetable variable that is within the update range of the to-be-created timetable plan, by employing the change restriction constraint as a constraint condition [see at least Paragraph 0027 for reference to system further includes a modify component that optimizes the time table based upon the aggregated information and adjusts (e.g., modifies) at least one of a dwell time for a vehicle located within a terminal, a departure time for a vehicle located within a terminal, and/or speed profile for a vehicle for a terminal; Paragraph 0033 for reference to the models being utilized to create and energy model for an environment in which two or more trains are to be synchronized with an optimized timetable; Paragraph 0037 for reference to the trigger including threshold values or triggers that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to the method updating the modified timetable based upon the threshold value or the tracking of the vehicles]
as a result of the executing, if a plan creation algorithm that does not yield an executable timetable plan is present, the computing device re-executes the plan creation algorithm in a state of alleviating the intensity of the change restriction constraint, regarding the timetable plan that has obtained by the re- executing [see at least Paragraph 0050 for reference to every iteration of the genetic algorithm being computed resulting in an objective function; Paragraph 0265 for reference to the adjusted default timetable being updated in real time to synchronize; Figure 8 and related text regarding item 850 ‘UPDATE THE ADJUSTED DEFAULT TIMETABLE IN REAL TIME IN ORDER TO SYNCHRONIZE BRAKE TIME FOR A VEHICLE AND AN ACCELERATION TIME FOR A VEHICLE BY CHANGING AT LEAST ONE OF A DEPARTURE TIME OF A VEHICLE, A DWELL TIME OF A VEHICLE, OR A SPEED PROFILE OF A VEHICLE’]
if an initial change restriction constraint that does not undergo the alleviating is not achieved based on an achievement status of the applied change restriction constraint, the computing device stores the initial change restriction constraint as an intensity-change-desired constraint [see at least Paragraph 0051 for reference to the algorithm never reaching non satisfiability as it is stayed in tolerable intervals; Paragraph 0088 for reference to parameters being modified to minimize the overall energy consumption; Paragraph 0092 for reference to constraints can be unsatisfied during the process of optimization]
the computing device stores the obtained timetable plan as a result timetable plan [see at least Paragraph 0092 for reference to constraints can be unsatisfied during the process of optimization but the final optimized timetable must satisfy all the constraints, or the timetable will be considered unfeasible]
Regarding claim 10, the claim recites limitations already addressed by the rejection of claim 5.
Claim 12
Regarding Claim 12, Fournier discloses the following:
A transportation plan system comprising [see at least Paragraph 0031 for reference to the system can create a timetable for two or more vehicles as well as optimize an existing timetable for two or more disparate vehicles; Figure 1 and related text regarding the system for optimizing energy consumption by synchronizing a first vehicle and a second vehicle; Figure 3 and related text regarding the system for controlling two or more vehicles based upon an optimized timetable that conserves energy by synchronizing a first vehicle and a second vehicle; Figure 4 and related text regarding a system for creating an optimized timetable offline and employing such optimized timetable online to conserve energy by synchronizing a first vehicle and a second vehicle]
a timetable plan creation system including a storage device that stores: first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute an timetable plan of a transport service [see at least Paragraph 0027 for reference to the data collector aggregating static and/or dynamic input; Paragraph 0030 for reference to the data collector aggregating information related to the timetable, a static input, and/or dynamic input; Paragraph 0030 for reference to static input including a Quality of Service (QoS) constraint, a constraint, an energy model, a tolerance, an energy profile, a network topology, an electric efficiency, an origin/destination matrix, a portion of a timetable, an energy transportation, a loss of energy, among others; Paragraph 0031 for reference to a timetable being created which takes into account at least one of a security constraint, a quality of service constraint, the issue of energy consumption, and the like; Paragraph 0042 for reference to tables being created to maximize quality of service, security and other constraints; Figures 1, 2, and 4 and related text regarding item 120 ‘data collector’]
second information that contains a creation algorithm for creating the timetable plan [see at least Paragraph 0027 for reference to the system including a modify component that optimizes the timetable based upon the aggregated information; Paragraph 0028 for reference to the system being computer-implemented via software such that the modify component adjusts a timetable to create the optimized timetable; Figure 1 and related text regarding item 130 ‘modify component’; Figure 4 and related text regarding item 430 ‘modify component’]
third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan, the timetable variables to be updated by the plan creation algorithms, and the evaluation index being one to be improved by executing the plan creation algorithms [see at least Paragraph 0037 for reference to the monitor tracking the vehicles in comparison with at least one of the optimized timetable and/or measured amount of energy; Paragraph 0266 for reference to the method including tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy]
fourth information that contains information on a desired change of the intensity of the constraint of the first information [see at least Paragraph 0037 for reference to the trigger including threshold values that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to tracking the vehicles in comparison with at least one of the modified timetable or a measured amount of energy, monitoring a threshold value related to the measured amount of energy]
a computing device that executes: a constraint generation process for generating a constraint with an intensity, based on the first information and the fourth information, the constraint being one generated for each of the timetable variables of a to-be-created timetable plan [see at least Paragraph 0028 for reference to the system being computer-implemented via software such that the modify component adjusts a timetable to create the optimized timetable; Paragraph 0031 for reference to a timetable being created which takes into account at least one of a security constraint, a quality of service constraint, the issue of energy consumption, and the like; Paragraph 0042 for reference to tables being created to maximize quality of service, security and other constraints; Figure 1 and related text regarding item 130 ‘modify component’; Figure 4 and related text regarding item 430 ‘modify component’]
a plurality of plan creation algorithms based on the third information, the plan creation algorithms being for improving a quality of the to-be-created timetable plan and each plan creation algorithms are composed of a plurality of optimization models [see at least Paragraph 0027 for reference to the modify component generating an optimized timetable wherein the optimized timetable improves energy consumption; Paragraph 0032 for reference to the system can include a model generator that creates energy model(s) that can be collected by the data collector and further utilized by the modify component; Paragraph 0040 for reference to a genetic algorithm being used to minimize an objective function – corresponding to the global energy consumption over a time horizon – computed with a liner program; Paragraph 0101-0102 for reference to the algorithmic approaches to model energy flows in the railway network wherein different formulations can be inferred regarding the topology of the real system one wants to model and to the simplifications one has to make to be able to optimize the model in reasonable time; Paragraph 0180 for reference to genetic algorithms (GAs) including instantiate a population of timetables slightly different from the initial one, classify the timetables, mate them (e.g., crossover), mutate them, and go back to instantiating a population of timetables until termination criterion]
a plan creation process for creating a new timetable plan by executing each of the plan creation algorithms, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process being applied to each of the plan creation algorithm [see at least Paragraph 0027 for reference to system further includes a modify component that optimizes the time table based upon the aggregated information and adjusts (e.g., modifies) at least one of a dwell time for a vehicle located within a terminal, a departure time for a vehicle located within a terminal, and/or speed profile for a vehicle for a terminal; Paragraph 0033 for reference to the models being utilized to create and energy model for an environment in which two or more trains are to be synchronized with an optimized timetable; Paragraph 0037 for reference to the trigger including threshold values or triggers that will indicate whether or not the modify component will be utilized to update the optimized timetable based on the tracked information; Paragraph 0266 for reference to the method updating the modified timetable based upon the threshold value or the tracking of the vehicles]
a traffic control system configured to: acquire the timetable plan from the timetable plan creation system, and control an operation of a mobile resource in the transport service, based on the timetable plan [see at least Paragraph 0034 for reference to the system including a controller that can implement a control to the vehicles based at least in part upon the generated optimized timetable; Paragraph 0035 for reference to the controller can include an automatic component (not shown) that will directly implement controls based upon a change identified in the optimized timetable; Figure 3 and related text regarding a system for controlling two or more vehicles based upon an optimized timetable that conserves energy by synchronizing a first vehicle and a second vehicle]
a resource management system configured to: acquire the timetable plan and the fourth information from the timetable plan creation system, and perform management of the mobile resource in the transport service, based on the timetable plan and the fourth information [see at least Paragraph 0035 for reference to the control including a notification component and/or a buffer component which provide a signal, message, or an instruction to the human operator as well as mitigate human delay to implement the optimized timetable; Figure 3 and related text regarding a system for controlling two or more vehicles based upon an optimized timetable that conserves energy by synchronizing a first vehicle and a second vehicle]
While Fournier discloses the limitations above, it does not disclose an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information and each plan creation algorithms are composed of a plurality of optimization models having an execution order.
However, Doner discloses the following:
a timetable plan creation system including a storage device that stores: first information that contains information regarding a constraint and an intensity of the constraint, the constraint being generated for each of a plurality of timetable variables that constitute an timetable plan of a transport service [see at least Paragraph 0022 for reference to a system for implementing a yard performance model; Paragraph 0022 for reference to the system including a computer which includes a processor for executing all functions of computer and a memory storage device for storing data and algorithms and a databased for storing specific additional data; Paragraph 0022 for reference to inputs including queries, parameters, and data related to yard performance; Paragraph 0022 for reference to in response to yard master’s inputs, computer utilizes memory and databased to solve equations and execute algorithms implemented in the yard performance model; Paragraph 0038 for reference to the yard parameter, input schedule and output schedule can be saved within system for later reuse; Figure 1 and related text regarding a system used to implement the railyard performance model including item 30 ‘memory storage device’ and item 34 ‘database’]
third information that contains information for associating a timetable variable of the timetable plan and a measure of an evaluation index of the timetable plan [see at least Paragraph 0039 for reference to yard topology parameters being based on the capacity of the subyards in terms of railcars wherein the initial levels of cars in each yard are determined before any simulation begins based on those cars in the receive and departure yard; Paragraph 0046 for reference to schedule parameters defining a train schedule and including the number of trains the schedule will contain, the total time interval for the schedule, whether or not inbound train arrival times will be perturbed normally about their nominal values, a number assigned as a train ID, the number of cars in the train, the expected arrival time of the train, offset from the beginning of the simulation interval, and a standard deviation about inbound train arrival time, which will be used with a normal distribution to vary train arrival times about their specified arrival times when the variable input schedule mode is chosen]
an algorithm selection process for selecting a plurality of plan creation algorithms based on the third information, the plan creation algorithms being for improving a quality of the to-be-created timetable plan and each plan creation algorithms are composed of a plurality of optimization models having an execution order [see at least Paragraph 0006 for reference to the method of allocating the available resources and services within the railyard in a given time period to optimize the flow of a collection of trains; Paragraph 0022 for reference to In response to the yard master’s inputs, computer utilizes processor, memory, and database to solve equations and execute algorithms implemented in the yard performance model; Paragraph 0038 for reference to the selection of an algorithm being static, dynamic headend first or backlog first based on the task load and labor movements during the simulation; Paragraph 0055 for reference to the yard performance model being best described by partitioning the performance model into submodels; Examiner noting that the “static, dynamic headend first, or backlog first” being analogous to the claimed “execution order”]
a plan creation process for creating a new timetable plan by executing each of the plan creation has algorithms that have been selected in the algorithm selection process, the execution of each of the plan creation algorithms including applying the constraint that has been generated in the constraint generation process being applied to each of the plan creation algorithm [see at least Paragraph 0055 for reference to the yard performance model calculating the initial task flow rates based on an initial state of train schedules; Paragraph 0137 beginning “A method in accordance with Claim 4 wherein said step of determining” for reference to the determination of a train schedule including calculating a train schedule based on the computed task flow rates; Paragraph 0137 beginning “A system for managing railcar movement in a railyard” for reference to determining if a train schedule can be met based on the simulated yard task flow; Claim 4 and related text regarding the railyard performance algorithm comprising the steps of computing task flow rates based on the updated task backlogs; Claim 5 and related text regarding the calculating a train schedule based on the computed task flow rates]
Before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify the timetable method of Fournier to include the algorithm selection of Doner. Doing so would assist in expediting and simplifying the process of moving railcars through a railyard from arrival to departure, as stated by Doner (Paragraph 0002).
Claim(s) 4 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Fournier (U.S 2014/0012454 A1) in view of Doner (US 2002/0082814 A1), as applied in claims 1 and 6, in view of Wang (CN109785072A).
Claims 4 and 9
While the combination of Fournier and Doner disclose the limitations above, regarding Claim 4, Fournier discloses the following:
the computing device acquires the to-be-created timetable plan and a current value of an evaluation index of the to-be- created timetable plan [see at least Paragraph 0059 for reference to the system using as input the current timetable of a line including all possible regulation constraints like headways]
the computing device acquires an aim value relating to the evaluation index and a changeable variable [see at least Paragraph 0189 for reference to different quantities being modified to optimize and given objective function including: departure times, dwell times, and/or speed profiles; Paragraph 0262 for reference to a determination of an objective function value]
the computing device extracts the plan creation algorithm permitted by the changeable variable, based on the timetable variable included in the third information [see at least Paragraph 0027 for reference to the modify component generating an optimized timetable wherein the optimized timetable improves energy consumption; Paragraph 0040 for reference to a genetic algorithm being used to minimize an objective function – corresponding to the global energy consumption over a time horizon – computed with a liner program; Paragraph 0101-0102 for reference to the algorithmic approaches to model energy flows in the railway network wherein different formulations can be inferred regarding the topology of the real system one wants to model and to the simplifications one has to make to be able to optimize the model in reasonable time]
While Fournier discloses the limitations above, it does not disclose wherein the algorithm selection process, the computing device calculates a relative distance that is to the aim value from the current value for each of the evaluation index, using the aim value and the current value of the evaluation index; the computing device sets a score for each of the extracted plan creation algorithm, using the relative distance and information that is included in the third information and that is on an improvement effect; and the computing device selects the plan creation algorithm that has a relatively higher score, as a to-be-currently-applied algorithm.
However, Wang discloses the following:
wherein the algorithm selection process, the computing device calculates a relative distance that is to the aim value from the current value for each of the evaluation index, using the aim value and the current value of the evaluation index [see at least Paragraph 0078 for reference to the system determining the Euclidian distance between the candidate value score set and exporting the candidate value score collection found Close corresponding probability value set; Examiner notes the ‘Euclidian distance’ as analogous to the ‘relative distance’]
the computing device sets a score for each of the extracted plan creation algorithm, using the relative distance and information that is included in the third information and that is on an improvement effect [see at least Paragraph 0088 for reference to sample candidate of product is worth score, and accurate sample candidate value score is accounted for determined sample candidate and is worth score wherein the ratio of sum is determined as the accuracy rate that sample candidate determined by the algorithm is worth score; Paragraph 0090 for reference to each subset in obtained at least two subclass It closes, the highest algorithm of accuracy rate is determined from the subclass]
the computing device selects the plan creation algorithm that has a relatively higher score, as a to-be-currently-applied algorithm [see at least Paragraph 0089 for reference to based on identified accuracy rate, selection algorithm is as algorithm corresponding with markup information from algorithm set; Paragraph 0090 for reference to each subset in obtained at least two subclass It closes, the highest algorithm of accuracy rate is determined from the subclass]
Before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify the timetable creation process of Fournier to include the algorithm selection method of Wang. Doing so would accurately characterize the value of target product, therefore being directed to the terminal pushed information of user can be improved Property, as stated by Wang (Paragraph 0142).
Regarding claim 9, the claim recites limitations already addressed by the rejection of claim 4.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Aminu, Abdulaziz, et al. "Design and implementation of an automatic examination timetable generation and invigilation scheduling system using genetic algorithm." 2019 2nd international conference on applied engineering (ICAE). IEEE, 2019.
DOCUMENT ID
INVENTOR(s)
TITLE
DE102007047474 A1
Erhard Karl-Heinz
Timetable Generation Process For Traffic Systems With Consideration of Time Limits
US 2004/0111309 A1
Matheson et al.
Resource Schedule For Scheduling Rail Way Train Resources
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/KRISTIN E GAVIN/Primary Examiner, Art Unit 3624
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