The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Notice to Applicant
In response to the communication received on 07/15/2025, the following is a Non-Final Office Action for Application No. 19269393.
Status of Claims
Claims 1-20 are pending.
Drawings
The applicant’s drawings submitted on 07/15/2025 are acceptable for examination purposes.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 07/15/2025 has been acknowledged. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of applicant’s claim for priority based on: 19269393 filed 07/15/2025 is a Continuation of 18673181, filed 05/23/2024, now U.S. Patent # 12358543 and having 1 RCE-type filing therein.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over the claims of U.S. Patent No. US 12358543 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because: referring to MPEP 804 II.B.2. Anticipation Analysis, “The claim under examination is not patentably distinct from the reference claim(s) if the claim under examination is anticipated by the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 1052, 29 USPQ2d 2010, 2015-16 (Fed. Cir. 1993). This type of nonstatutory double patenting situation arises when the claim being examined is, for example, generic to a species or sub-genus claimed in a conflicting patent or application, i.e., the entire scope of the reference claim falls within the scope of the examined claim.” Here, claim under examination is anticipated by the reference claim(s) since the claims recite substantially similar limitations. Particularly, the entire scope of independent claims of Patent US 12358543 B2 falls within the scope of independent claims of the present application.
The following is a mapping of the claims of the Patent against the claims of the present application:
Present Application
Patent US 12358543 B2
Identified differences and rationale as to why that does not amount to a patentable difference.
A system comprising: a memory configured to store outbound train schedule data; and a processor coupled to the memory and configured to execute computer program instructions, wherein the configuration of the one or more computer processors to execute the computer program instructions includes configuration to spawn a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at least a portion of a second optimization model, and to spawn a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at least a portion of the second optimization model, wherein the first computer process and the second computer process are spawned concurrently, wherein the one or more computer processors is fuirther configured to execute the computer program instructions to:access the outbound train schedule data;determine, using a first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon;after determining the first list of train block assignments using the first optimization model, determine whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimization model indicates a number of train blocks that remain unassigned to a classification track;in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, display the first list of train block assignments generated by the first optimization model on an electronic display;
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in response to determining that the unassigned train block volume from the first optimization model is greater than zero:determine, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; and display the second list of train block assignments generated by the second optimization model on the electronic display.
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A system comprising:one or more memory units configured to store outbound train schedule data; andone or more computer processors communicatively coupled to the one or more memory units and configured to execute computer program instructions, wherein the configuration of the one or more computer processors to execute the computer program instructions includes configuration to spawn a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model, and to spawn a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model, wherein the first computer process and the second computer process are spawned concurrently, wherein the one or more computer processors is further configured to execute the computer program instructions to:access the outbound train schedule data;determine, using the first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon;after determining the first list of train block assignments using the first optimization model, determine whether an unassigned train block volume from the first optimization model isgreater than zero, wherein the unassigned train block volume from the first optimization model indicates a number of train blocks that remain unassigned to a classification track after using the first optimization model to determine the first list of train block assignments;in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, display the first list of train block assignments generated by the first optimization model on an electronic display;in response to determining that the unassigned train block volume from the first optimization model is greater than zero:determine, using the second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; and display the second list of train block assignments generated by the second optimization model on the electronic display;wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; and one or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon.
Patent has additional limitations of: wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; andone or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon. This is not a patentable difference because the present claim without this limitation is anticipated by the patented claim.
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A method by a computing system for assigning train blocks at a railroad merchandise yard, the method comprising: spawning a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model; spawning, concurrently with the spawning of the first computer process, a second computer process configured to execute a second set of computer program instructions 4 including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model; accessing outbound train schedule data; determining, using a first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon; after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimizationmodel indicates a number of train blocks that remain unassigned to a classification track; in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display; in response to determining that the unassigned train blockvoluime from the first optimization model is greater than zero:determining, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; anddisplaying the second list of train block assignments generated by the second optimizationmodel on the electronic display.
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A method by a computing system for assigning train blocks at a railroad merchandise yard, the computing system including one or more processors configured to execute computer program instructions, the method comprising: spawning a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model; spawning, concurrently with the spawning of the first computer process, a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model; accessing outbound train schedule data; determining, using the first optimization model and the outbound train schedule data, a firstlist of train block assignments for a planning horizon;after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimization model indicates a number of train blocks that remain unassigned to a classification track after using the first optimization model to determine the first list of train block assignments;in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display;in response to determining that the unassigned train block volume from the first optimization model is greater than zero:determining, using the second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; anddisplaying the second list of train block assignments generated by the second optimization model on the electronic display;wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; andone or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon.
Patent has additional limitations of: wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; andone or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon. This is not a patentable difference because the present claim without this limitation is anticipated by the patented claim.
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One or more computer-readable non-transitory storage media embodying instructions that, when executed by a processor, cause the processor to perform operations comprising: spawning a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model; spawning, concurrently with the spawning of the first computer process, a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model; accessing outbound train schedule data; determining, using a first optimizationmodel and the outbound train schedule data, a first list of train block assignments for a planning horizon; after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimizationmodel indicates a number of train blocks that remain unassigned to a classification track;8 in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display; in response to determining that the unassigned train block volume from the first optimizationmodel is greater than zero:determining, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; anddisplaying the second list of train block assignments generated by the second optimizationmodel on the electronic display.
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One or more computer-readable non-transitory storage media embodying instructions that, when executed by a processor, cause the processor to spawn a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model, and to spawn a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model, wherein the first computer process and the second computer process are spawned concurrently, and wherein operations of the first set of operations and the second set of operations include: accessing outbound train schedule data;determining, using the first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon;after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimization model indicates a number of train blocks that remain unassigned to a classification track after using the first optimization model to determine the first list of train block assignments;in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display;in response to determining that the unassigned train block volume from the first optimization model is greater than zero:determining, using the second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; anddisplaying the second list of train block assignments generated by the second optimization model on the electronic display;wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; andone or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon.
Patent has additional limitations of: wherein the first and second lists of train block assignments each comprise:a plurality of classification tracks of a classification bowl;a plurality of time periods of the planning horizon; andone or more of a plurality of train blocks that are assigned to each classification track for each time period of the planning horizon. This is not a patentable difference because the present claim without this limitation is anticipated by the patented claim.
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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 1-20 are rejected under 35 U.S.C. 101 as directed to non-statutory subject matter.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. In adhering to the 2019 PEG, Step 1 is directed to determining whether or not the claims fall within a statutory class. Herein, the claims fall within statutory class of process or machine or manufacture. Hence, the claims qualify as potentially eligible subject matter under 35 U.S.C §101. With Step 1 being directed to a statutory category, the 2019 PEG flowchart is directed to Step 2. Step 2 is the two-part analysis from Alice Corp. (also called the Mayo test). The 2019 PEG makes two changes in Step 2A: It sets forth new procedure for Step 2A (called “revised Step 2A”) under which a claim is not “directed to” a judicial exception unless the claim satisfies a two-prong inquiry. The two-prong inquiry is as follows: Prong One: evaluate whether the claim recites a judicial exception (an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon). If claim recites an exception, then Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. The claim(s) recite(s) the following abstract idea indicated by non-boldface font and additional limitations indicated by boldface font:
1. A system comprising: a memory configured to store outbound train schedule data; and a processor coupled to the memory and configured to execute computer program instructions, wherein the configuration of the one or more computer processors to execute the computer program instructions includes configuration to spawn a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at least a portion of a second optimization model, and to spawn a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at least a portion of the second optimization model, wherein the first computer process and the second computer process are spawned concurrently, wherein the one or more computer processors is fuirther configured to execute the computer program instructions to:access the outbound train schedule data;determine, using a first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon;after determining the first list of train block assignments using the first optimization model, determine whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimization model indicates a number of train blocks that remain unassigned to a classification track;in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, display the first list of train block assignments generated by the first optimization model on an electronic display;in response to determining that the unassigned train block volume from the first optimization model is greater than zero:determine, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon;and display the second list of train block assignments generated by the second optimization model on the electronic display.
[or]
9.A method by a computing system for assigning train blocks at a railroad merchandise yard, the method comprising: spawning a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model; spawning, concurrently with the spawning of the first computer process, a second computer process configured to execute a second set of computer program instructions 4 including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model; accessing outbound train schedule data; determining, using a first optimization model and the outbound train schedule data, a first list of train block assignments for a planning horizon; after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimizationmodel indicates a number of train blocks that remain unassigned to a classification track; in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display; in response to determining that the unassigned train blockvoluime from the first optimization model is greater than zero:determining, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; anddisplaying the second list of train block assignments generated by the second optimizationmodel on the electronic display.
[or]
17. One or more computer-readable non-transitory storage media embodying instructions that, when executed by a processor, cause the processor to perform operations comprising: spawning a first computer process configured to execute a first set of computer program instructions including instructions to implement one or more of at least a portion of a first optimization model and at last a portion of a second optimization model; spawning, concurrently with the spawning of the first computer process, a second computer process configured to execute a second set of computer program instructions including instructions to implement one or more of the at least a portion of the first optimization model and the at last a portion of the second optimization model; accessing outbound train schedule data; determining, using a first optimizationmodel and the outbound train schedule data, a first list of train block assignments for a planning horizon; after determining the first list of train block assignments using the first optimization model, determining whether an unassigned train block volume from the first optimization model is greater than zero, wherein the unassigned train block volume from the first optimizationmodel indicates a number of train blocks that remain unassigned to a classification track;8 in response to determining that the unassigned train block volume from the first optimization model is not greater than zero, displaying the first list of train block assignments generated by the first optimization model on an electronic display;in response to determining that the unassigned train block volume from the first optimizationmodel is greater than zero:determining, using a second optimization model and the outbound train schedule data, a second list of train block assignments for the planning horizon; and displaying the second list of train block assignments generated by the second optimization model on the electronic display.
Per Prong One of Step 2A, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity. Particularly, the identified recitation falls within the Mental Processes including concepts performed in the human mind (including an observation, evaluation judgment, opinion) and/or Certain Methods of Organizing Human Activity including managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules of instructions). Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The processor and/or memory medium is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing/transmitting data. This generic processor and/or memory medium limitation is no more than mere instructions to apply the exception using a generic computer component. Further, displaying the second list of train block assignments generated by the second optimization model on the electronic display by a processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, since the claims are directed to the determined judicial exception in view of the two prongs of Step 2A, the 2019 PEG flowchart is directed to Step 2B. Therein, the additional elements and combinations therewith are examined in the claims to determine whether the claims as a whole amounts to significantly more than the judicial exception. It is noted here that the additional elements are to be considered both individually and as an ordered combination. In this case, the claims each at most comprise additional elements of: computing system, processor and memory medium. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, displaying the second list of train block assignments generated by the second optimization model on the electronic display by a processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot provide an inventive concept in Step 2B (or, looking back to Step 2A, cannot integrate a judicial exception into a practical application). For further support, the Applicant’s specification supports the claims being directed to use of a generic computer/memory type structure at ¶0130 wherein processor 1402 may include one or more arithmetic logic units (ALUs); be a multi- core processor; or include one or more processors 1402. Taken as an ordered combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations are directed to limitations referenced in Alice Corp. that are not enough to qualify as significantly more when recited in a claim with an abstract idea include, as a non-limiting or non-exclusive examples: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
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ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
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iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or
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v. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook. The courts have recognized the following computer functions inter alia to be well-understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations; receiving, processing, and storing data (e.g., the present claims); electronically scanning or extracting data; electronic recordkeeping; automating mental tasks (e.g., process/machine/manufacture for performing the present claims); and receiving or transmitting data (e.g., the present claims). The dependent claims do not cure the above stated deficiencies, and in particular, the dependent claims further narrow the abstract idea without reciting additional elements that integrate the exception into a practical application of the exception or providing significantly more than the abstract idea. Since there are no elements or ordered combination of elements that amount to significantly more than the judicial exception, the claims are not eligible subject matter under 35 USC §101. Thus, 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. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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Models for Railway Timetable Optimization: Applicability and Applications in Practice
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KURTIS GILLS whose telephone number is (571)270-3315. The examiner can normally be reached on M-F 8-5 PM. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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/KURTIS GILLS/Primary Examiner, Art Unit 3624
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