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 10/10/2024, the following is a Non-Final Office Action for Application No. 18911420.
Status of Claims
Claims 1-20 are pending.
Drawings
The applicant’s drawings submitted on 10/10/2024 are acceptable for examination purposes.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on 10/10/2024, 12/23/2025, 03/01/2026, 04/16/2026, 05/01/2026 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: 18911420 filed 10/10/2024 is a Continuation in Part of 18501608 , filed 11/03/2023 ,now U.S. Patent # 12217199 and having 1 RCE-type filing therein.
Claim Interpretation
5. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: controller in independent claims 1, 10 and 20, and dependents therefrom. The specification at ¶0061 states “As shown in FIG. 2, server 110 includes processor 111, memory 112, time-expanded network 120, chassis optimization system 121, resources optimization system 129, and database 114. Processor 111 may comprise a processor, a microprocessor, a controller, a microcontroller, a plurality of microprocessors, an application-specific integrated circuit (ASIC), an application-specific standard product (ASSP), or any combination thereof, and may be configured to execute instructions to perform operations in accordance with the disclosure herein.” The specification at ¶00115 states “the processor may be any conventional processor, controller, microcontroller, or state machine.”
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 method of optimizing utilization of chassis resources associated with a hub, comprising: obtaining an optimized operating schedule including a consolidated time-space network representing a consolidation operational stream and a deconsolidated time-space network representing a deconsolidation operational stream over a planning horizon, wherein the optimized operating schedule includes a unit traffic prediction expected to arrive at the hub at each time increment of a planning horizon of the optimized operating schedule; determining one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon; synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon to generate one or more chassis recommendations to pair chassis supply events with chassis consumption events of the consolidation operational stream and the deconsolidation operational stream over the planning horizon; including the one or more chassis recommendations to pair chassis supply events with chassis consumption events into the optimized operating schedule; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause a first container to be removed from a chassis as part of the consolidation operational stream and to cause a second container to be placed onto the chassis as part of the deconsolidation operational stream in accordance with the one or more chassis recommendations to pair chassis supply events with chassis consumption events.
[OR]
10. A system configured to optimize utilization of chassis resources in a train yard, comprising: at least one processor; and a memory operably coupled to the at least one processor and storing processor-readable code that, when executed by the at least one processor, is configured to perform operations including: obtaining an optimized operating schedule including a consolidated time-space network representing a consolidation operational stream and a deconsolidated time-space network representing a deconsolidation operational stream over a planning horizon, wherein the optimized operating schedule includes a unit traffic prediction expected to arrive at the hub at each time increment of a planning horizon of the optimized operating schedule; determining one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon; synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon to generate one or more chassis recommendations to pair chassis supply events with chassis consumption events of the consolidation operational stream and the deconsolidation operational stream over the planning horizon; including the one or more chassis recommendations to pair chassis supply events with chassis consumption events into the optimized operating schedule; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause a first container to be removed from a chassis as part of the consolidation operational stream and to cause a second container to be placed onto the chassis as part of the deconsolidation operational stream in accordance with the one or more chassis recommendations to pair chassis supply events with chassis consumption events.
[OR]
19. A computer-based tool for optimizing utilization of chassis resources in a train yard, the computer-based tool including non-transitory computer readable media having stored thereon computer code which, when executed by a processor, causes a computing device to perform operations comprising: obtaining an optimized operating schedule including a consolidated time-space network representing a consolidation operational stream and a deconsolidated time-space network representing a deconsolidation operational stream over a planning horizon, wherein the optimized operating schedule includes a unit traffic prediction expected to arrive at the hub at each time increment of a planning horizon of the optimized operating schedule; determining one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon; synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon to generate one or more chassis recommendations to pair chassis supply events with chassis consumption events of the consolidation operational stream and the deconsolidation operational stream over the planning horizon; including the one or more chassis recommendations to pair chassis supply events with chassis consumption events into the optimized operating schedule; and automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause a first container to be removed from a chassis as part of the consolidation operational stream and to cause a second container to be placed onto the chassis as part of the deconsolidation operational stream in accordance with the one or more chassis recommendations to pair chassis supply events with chassis consumption events.
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 controller, container, chassis, train yard, non-transitory computer readable media, memory, processor, and/or computing device 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 controller, container, chassis, train yard, non-transitory computer readable media, memory, processor, and/or computing device limitation is no more than mere instructions to apply the exception using a generic computer component. Further, generating a signal via a controller, container, chassis, train yard, non-transitory computer readable media, memory, processor, and/or computing device 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: controller, container, chassis, train yard, non-transitory computer readable media, memory, processor, and computing device. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, generating a signal via a controller, container, chassis, train yard, non-transitory computer readable media, memory, processor, and/or computing device 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 ¶0061 wherein “processor 111 may comprise a processor, a microprocessor, a controller, a microcontroller, a plurality of microprocessors, an application-specific integrated circuit (ASIC), an application-specific standard product (ASSP), or any combination thereof”. 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.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 of this title, 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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gabrielson (WO 2009018437 A1) hereinafter referred to as Gabrielson in view of Scharaswak et al. (US 20160300186 A1) hereinafter referred to as Scharaswak.
Gabrielson teaches:
Claim 1. A method of optimizing utilization of chassis resources associated with a hub, comprising:
obtaining an optimized operating schedule including a consolidated time-space network representing a consolidation operational stream and a deconsolidated time-space network representing a deconsolidation operational stream over a planning horizon, wherein the optimized operating schedule includes a unit traffic prediction expected to arrive at the hub at each time increment of a planning horizon of the optimized operating schedule (¶0036 the business rule that inland point intermodal (IPI) orders should only use 40 foot shipping containers is optionally used in the Gateway Balancing Module 26 to avoid potential chassis limitations for drayage from a de- consolidator. ¶0053 The Central Consolidation Subcomponent 84 includes means for consolidating the FCA partial loads that were not selected for field consolidation and means for consolidating freight on board (FOB) partial loads. ¶0064 In some embodiments, the booking request and routing instructions are provided with a dispatch report to the inland freight carrier. The routing instructions optionally include the scheduled appointment times for each pickup along a multi-stop route, the sequence of pickups at vendor locations along the multi-stop route, all necessary addresses in appropriate languages (English as well as the local language, for example), purchase order information, quantities that are to be to picked up at each vendor location, and other information as desired. The inland freight carrier then picks up the partial container load freight shipments and loads them, for example, onto a truck container or other appropriate shipping container. The Routing & Booking Component 44 also optionally includes means for assigning a container shipment carrier and vessel/voyage for planned loads, such as one or more interactive menus similar to those previously described. ¶0073 The running tally of containers fulfilling MQC obligations to carriers is updated and recorded. For example, the MQC Balancing Module 22 optionally includes one or more databases for storing MQC data and processors for receiving and updating the MQC data. The MQC Balancing Module 24 is optionally integrated and/or interactive with Modules 22, 26 sharing information and/or process tasks as desired. [0074 The Gateway Balancing Module 22 assists with balancing incoming container shipments between gateways according to the loading of gateway resources. FIG. 10 is a schematic showing various importation gateways. For reference, a "gateway" for incoming shipments of goods to be delivered to retail locations 100 is supported by ports of arrival 102 (including inland ports of arrival, such as airports or ocean carrier ports located inland, e.g., Chicago ocean carrier ports on Lake Michigan), de-consolidators 104, import warehouses, trucking, and distribution centers 106, for example. In general terms, the Gateway Balancing Module 22 provides means for balancing shipments of a plurality of containers on one or more container shipment carriers between a plurality of associated gateways. ¶0074 The Gateway Balancing Module 22 assists with balancing incoming container shipments between gateways according to the loading of gateway resources. FIG. 10 is a schematic showing various importation gateways. ¶0094 The Container Complexity Profile 126 includes information relating to the relative complexity of a container in terms of de-consolidation, or a container de- consolidation complexity factor. For reference, one or more factors relating to de- consolidation complexity are optionally combined to evaluate consolidation complexity. In particular, a variety of factors play a role in how much time/effort container de- consolidation (as well as consolidation) requires. For example, in some embodiments, a container consolidation factor is employed during inland freight management, for example during load planning & routing, to efficiently accomplish field consolidation in an analogous manner to container de-consolidation ¶0128 The gateway balancing process is optionally scheduled to be automatically performed at a predetermined time, for example daily. The gateway balancing process can also be initiated upon user demand, for example via the interactive menus. Subcomponent 164 sends the recommendation information to a repository, such as a networked database, for users to view summarized or detailed information as desired. In some embodiments, if the de-consolidation demand on a particular gateway exceeds the allocated de-consolidation capacity, the inbound demand, or order volume must be shifted to another de-consolidator and/or a request for additional de-consolidation capacity must be made.);
determining one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon (¶0036 the business rule that inland point intermodal (IPI) orders should only use 40 foot shipping containers is optionally used in the Gateway Balancing Module 26 to avoid potential chassis limitations for drayage from a de- consolidator. ¶0095 In some embodiments, a variety of factors are averaged or otherwise combined to rank all containers for a plurality of shipments associated with one or more gateways on a relative complexity scale. As will be described in greater detail below, the Balancing Recommendation Generation Component 1 14 accesses appropriate data, for example profile information, and calculates the container complexity factors. In some embodiments, a container with moderate de-consolidation complexity is optionally used as a starting point, or baseline complexity, with a base rating of 1.00. A more complex container has a higher rating, for example where a rating of 3.00 is equal to de- consolidating the contents of three containers even though it is one physical piece of equipment. A less complex container has a lower rating, for example of 0.05, the equivalent of one-twentieth of the average container.);
synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon to generate one or more chassis recommendations to pair chassis supply events with chassis consumption events of the consolidation operational stream and the deconsolidation operational stream over the planning horizon;including the one or more chassis recommendations to pair chassis supply events with chassis consumption events into the optimized operating schedule (¶0073 The running tally of containers fulfilling MQC obligations to carriers is updated and recorded. For example, the MQC Balancing Module 22 optionally includes one or more databases for storing MQC data and processors for receiving and updating the MQC data. The MQC Balancing Module 24 is optionally integrated and/or interactive with Modules 22, 26 sharing information and/or process tasks as desired. The Gateway Balancing Module 22 assists with balancing incoming container shipments between gateways according to the loading of gateway resources. FIG. 10 is a schematic showing various importation gateways. For reference, a "gateway" for incoming shipments of goods to be delivered to retail locations 100 is supported by ports of arrival 102 (including inland ports of arrival, such as airports or ocean carrier ports located inland, e.g., Chicago ocean carrier ports on Lake Michigan), de-consolidators 104, import warehouses, trucking, and distribution centers 106, for example. In general terms, the Gateway Balancing Module 22 provides means for balancing shipments of a plurality of containers on one or more container shipment carriers between a plurality of associated gateways. ¶0095 In some embodiments, a variety of factors are averaged or otherwise combined to rank all containers for a plurality of shipments associated with one or more gateways on a relative complexity scale. As will be described in greater detail below, the Balancing Recommendation Generation Component 1 14 accesses appropriate data, for example profile information, and calculates the container complexity factors. In some embodiments, a container with moderate de-consolidation complexity is optionally used as a starting point, or baseline complexity, with a base rating of 1.00. A more complex container has a higher rating, for example where a rating of 3.00 is equal to de- consolidating the contents of three containers even though it is one physical piece of equipment); and
automatically sending, during execution of the optimized operating schedule, a control signal to a controller to cause a first container to be removed from a chassis as part of the consolidation operational stream and to cause a second container to be placed onto the chassis as part of the deconsolidation operational stream in accordance with the one or more chassis recommendations to pair chassis supply events with chassis consumption events (¶0092 The Change Preference Profile 122 also optionally includes information relating to the booking status of container shipments and timing when the Gateway Balancing Module 26 should no longer consider a container shipment as eligible for gateway balancing between the plurality of associated gateways. In some embodiments, the container shipment is no longer eligible for gateway balancing when the container shipment carrier (e.g., ocean or air carrier) sends a reservation confirmation for shipping the containers.).
Although not explicitly taught by Gabrielson, Scharaswak teaches in the analogous art of systems for vehicle fleet control:
obtaining an optimized operating schedule including a consolidated time-space network representing a consolidation operational stream and a deconsolidated time-space network representing a deconsolidation operational stream over a planning horizon, wherein the optimized operating schedule includes a unit traffic prediction expected to arrive at the hub at each time increment of a planning horizon of the optimized operating schedule (¶0097 In some implementations, a dedicated fleet control system such as dedicated fleet control system 104 of FIG. 1 may perform simultaneous route assignment and cost optimization operations using an example optimization model, labeled Model 1, that will now be described in connection with, for example, Tables 1 and 2 and FIG. 5. In particular, Table 1 below presents various terms that may be used in an example of an optimization model for simultaneous route assignment and cost optimization. In the Model 1 implementation, a new cost structure is utilized in the objective function of the model, and additional practical constraints are also applied to allow transportation providers to assign and route resources according to the decision factors that they value in practice. ¶0154 An overview of the comparison of Models 1, 2, and 3 is shown in Table 3 below. Table 3 demonstrates that using Model 1 results in a much more balanced decision process for minimizing costs and utilizing the dedicated fleet. Model 1 achieves the lowest travel cost compared to the other two models and, in this example, 62.3% of loads are allocated to dedicated fleet vehicles 110. In contrast, Model 2 over-utilized common carriers, a solution that may be unacceptable to some transportation providers based on low utilization of dedicated fleet vehicles 110. The additional weighting in Model 3 for assigning routes increases utilization of dedicated fleet resources relative to Model 2, but at a higher cost relative to Model 1. Finally, Model 1 combines the decision making into a single model. It is shown that automating the process into a single optimization model may achieve efficiencies and cost reductions that multi-objective (weighting) process of Model 3 may not be able to consistently achieve, even based on expert judgment. ¶0031 assignment systems and methods based on direct route costs for each shipment, may be supplemented by other factors or constraints such as timeliness of deliveries (e.g., customer service), the ability to return dedicated fleet drivers to their home depot at the end of each shift, the backhaul probability of each route (e.g., to reduce empty or less-that-full miles travelled on return routes), maximizing the utilization of dedicated assets (e.g., reducing or minimizing idle time and less-than-full miles for each vehicle of a dedicated fleet), and/or other real-time information such as vehicle mechanical issues (e.g., mechanical problems that can arise at any time), safety issues, fuel prices, oil prices, highway conditions such as traffic conditions and associated delays and/or road work or conditions and associated delays, accidents, etc);
including the one or more chassis recommendations to pair chassis supply events with chassis consumption events into the optimized operating schedule (¶0097 In some implementations, a dedicated fleet control system such as dedicated fleet control system 104 of FIG. 1 may perform simultaneous route assignment and cost optimization operations using an example optimization model, labeled Model 1, that will now be described in connection with, for example, Tables 1 and 2 and FIG. 5. In particular, Table 1 below presents various terms that may be used in an example of an optimization model for simultaneous route assignment and cost optimization. In the Model 1 implementation, a new cost structure is utilized in the objective function of the model, and additional practical constraints are also applied to allow transportation providers to assign and route resources according to the decision factors that they value in practice. ¶0100-0105 Routes 204/208 may each be referred to as a set of paired nodes 206 labeled as (i, j), which are used to define valid routes. In order to avoid unnecessary routes and decrease the number of variables, the following implementations of dedicated carrier constraints may be utilized for defining routes 204/208 in the Model 1 implementations: There is no valid route 204/208 from a delivery node 206 to another delivery node 206 There is no route 204/208 from depot return node (node 2) to any other node 206 From each pick-up node 206 there is only one route 204/208 to its corresponding delivery node 206 As discussed above, in other implementations, routing assignments can sometimes be performed with a single carrier model (e.g., a private carrier, a dedicated carrier, or a common carrier), instead of a combination of carriers. In still other implementations, models that do allow selection of different types of carriers can be used and may utilize direct costs in determining routing and carrier assignments. In still other implementations, multi-objective or multi-criteria decision making methods may be utilized for multi-carrier selection processes to allow integration of other decision factors into the process. However, in the Model 1 example, a particular cost model is provided that allows routing determinations and carrier assignments to be performed using a single objective model for carrier selection of routes ¶0171 As previously noted, a pick-up and delivery time window may be associated with each load. Providing a higher flexibility in time windows may give more freedom in scheduling the dedicated vehicle fleet. In some implementations, a flexibility factor % Flexibility may be applied to the time window as shown below: Deliverytime=Pickuptime+(Traveltime+Servicetime)*(1+% Flexibility) (Equation 17) The time window may, for example, be a maximum amount of allowable time between a pickup time and a delivery time for a particular load as described by the equation above. The flexibility factor may be applied to the maximum allowable time difference between the pickup time and the delivery time as shown. ¶0214 In this way, plan optimizer 836 generates a ranking of loads or shipments that may be moved from a dedicated fleet to a common carrier fleet based in part, for example, on real-time updated status information from communications circuitry 150 of each of vehicles 110. Plan optimizer 836 may proceed by evaluating each ranked load with consideration to real-time updated driver HOS to prevent a load from being assigned to a driver without HOS available (stage 1130). Stage 1130 may also receive input from stage 1116 from Phase A of plan optimizer 836. Plan optimizer 836 may then commit each load to a fleet that have driver HOS available and change the reference value from “B” to “ExCCChangeToFleet” (stage 1130) and the planning process may end (stage 1132).).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the systems for vehicle fleet control of Scharaswak with the system for transportation management of Gabrielson for the following reasons:
(1) a finding that there was some teaching, suggestion, or motivation, either in the references themselves or in the knowledge generally available to one of ordinary skill in the art, to modify the reference or to combine reference teachings, e.g. Gabrielson ¶0001 teaches that a need exists for improvements addressing the complexities of planning and executing the procurement and transportation of goods from vendors;
(2) a finding that there was reasonable expectation of success since the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference, e.g. Gabrielson Abstract teaches gateway balancing module balances shipments of a plurality of containers between a plurality of associated gateways and includes a determine demand subcomponent, a calculate containers subcomponent, a determine capacity subcomponent, and a generate balance recommendations subcomponent, and Scharaswak Abstract teaches systems and methods for control of a vehicle fleet system; and
(3) whatever additional findings based on the Graham factual inquiries may be necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness, e.g. Gabrielson at least the above cited paragraphs, and Scharaswak at least the inclusively cited paragraphs.
Therefore, it would be obvious to one skilled in the art at the time of the invention to combine the systems for vehicle fleet control of Scharaswak with the system for transportation management of Gabrielson. The rationale to support a conclusion that the claim would have been obvious is that "a person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and whether there would have been a reasonable expectation of success in doing so." DyStar Textilfarben GmbH & Co. Deutschland KG v. C.H. Patrick Co., 464 F.3d 1356, 1360, 80 USPQ2d 1641, 1645 (Fed. Cir. 2006). See MPEP 2143(G).
Gabrielson teaches:
Claim 2. The method of claim 1, wherein the unit traffic prediction includes a prediction of containers and chassis expected to arrive at the hub at each stage of the consolidation operational stream and a prediction of containers expected to arrive at the hub at each stage of the deconsolidation operational stream at time increment of the planning horizon of the optimized operating schedule (¶0085 For reference, a de-consolidator divides and sorts container contents from container shipments into smaller quantities for distribution. In some embodiments, each de-consolidator generally has a facility that serves one or more customers, one of which is the large retail entity (LRE). In some embodiments, the large retail entity (LRE) forecasts a minimum de-consolidation volume for one or more de-consolidators.The container de-consolidator capacity information includes a minimum quantity and minimum quantity threshold which is forecasted for the de-consolidator. The minimum quantity represents a target minimum amount to provide the de- consolidator and the minimum quantity threshold, expressed as a percentage, for example, represents a self-imposed maximum allowable downward deviation from the minimum quantity ¶0119 The Calculate Containers Subcomponent 152 includes means for handicapping, or adjusting, the forecasted volume containers that are to be shipped to a plurality of gateways. In particular, a handicapped demand, also described as an adjusted or weighted demand, for the gateways initially assigned to the container shipments is determined from the initial demand obtained using the Determine Demand Subcomponent 150. For example, two actual containers from one or more purchase orders to be shipped can be handicapped, or weighted, such that they are the equivalent of processing six standard containers of average complexity using complexity handicapping information from the Container Complexity Profile 126.).
Gabrielson teaches:
Claim 3. The method of claim 1, wherein synchronizing the consolidation operational stream and the deconsolidation operational stream over the planning horizon includes synchronizing ramping operations of the consolidation operational stream and deramping operations of the deconsolidation operational stream to generate the one or more chassis recommendations to pair chassis supply events with chassis consumption events (¶0119 The Calculate Containers Subcomponent 152 includes means for handicapping, or adjusting, the forecasted volume containers that are to be shipped to a plurality of gateways. In particular, a handicapped demand, also described as an adjusted or weighted demand, for the gateways initially assigned to the container shipments is determined from the initial demand obtained using the Determine Demand Subcomponent 150. ¶0122 The Determine Confirmed Demand Subcomponent 158 includes means for considering the confirmed demand and unconfirmed demand on the gateways represented by container shipment containers. The Determine Confirmed Demand Subcomponent 158 is adapted to filter the confirmed demand (demand represented by carriers who have already sent reservation confirmation for shipping) and/or unconfirmed demand (not yet confirmed for shipping by the carrier) for balancing eligibility according to the estimated time of arrival (ETA) at a gateway As previously referenced, the confirmed demand on a gateway is generally less eligible for balancing. In some embodiments, the estimated time of arrival at a particular gateway is determined relative to an estimated time of arrival at a de-consolidator of the gateway, which is some number of days (e.g., 2 days more) from the estimated time of arrival of a vessel at the gateway port of arrival. In some embodiments, the Determine Confirmed Demand Subcomponent 158 includes one or more interactive menus and associated algorithms, such as those previously described, utilized by the system user to calculate and evaluate confirmed and/or unconfirmed demand on gateway resources, including de-consolidation resources).
Gabrielson teaches:
Claim 4. The method of claim 3, wherein the one or more recommendations to pair chassis supply events with chassis consumption events include one or more recommendations to perform a ramping operations to release a chassis from a first container, and to perform a corresponding deramping operations to place a second container on the chassis (¶0119 The Calculate Containers Subcomponent 152 includes means for handicapping, or adjusting, the forecasted volume containers that are to be shipped to a plurality of gateways. In particular, a handicapped demand, also described as an adjusted or weighted demand, for the gateways initially assigned to the container shipments is determined from the initial demand obtained using the Determine Demand Subcomponent 150. ¶0122 The Determine Confirmed Demand Subcomponent 158 includes means for considering the confirmed demand and unconfirmed demand on the gateways represented by container shipment containers. The Determine Confirmed Demand Subcomponent 158 is adapted to filter the confirmed demand (demand represented by carriers who have already sent reservation confirmation for shipping) and/or unconfirmed demand (not yet confirmed for shipping by the carrier) for balancing eligibility according to the estimated time of arrival (ETA) at a gateway.).
Gabrielson teaches:
Claim 5. The method of claim 1, wherein the one or more capacity constraints associated with the chassis resource capacity of the hub include one or more of: availability of chassis of the chassis resource capacity; a type of the chassis of the chassis resource capacity; a size of the chassis of the chassis resource capacity; and chassis pool characteristics of the chassis of the chassis resource capacity (¶0035 The Equipment Profile 70 includes equipment information relating to the various components of the System 20. The Equipment Profile 70 includes availability information according to equipment categories, sizes, types, weight thresholds, maximum and minimum volume ranges, as well as other shipping equipment information. FIG. 4 is a schematic view of a data screen 90 showing some types of equipment information included with the Equipment Profile 70, although other equipment information is contemplated. ¶0039 The Booking Queue Profile 74 includes booking information relating to inland freight shipments that the Large Retail Entity (LRE) is responsible for building into container loads. This list of shipments is also described as the booking queue. The booking information, such as quantities, types of goods, whether loads are Container Yard (CY) loads vs. Container Freight Station (CFS) loads, as well as whether the large retail entity is responsible for shipping to port (FCA) or the vendor is responsible for shipping to port (FOB), and other booking information is a result of one or more vendor booking processes used by the Large Retail Entity (LRE). Although FCA and FOB are used as examples herein, it should be understood that use of other types of shipping information and designators, including all of those associated with internationally recognized Incoterms, are contemplated. ¶0056 the load summary 94 includes information such as a system designated container number, load ID, load status, the number of shipments comprising the load, the total cubic volume of the load, and others. In some embodiments, the size and type of equipment for the loads are selected on the load summary 94. In other embodiments, the size and type of equipment is selected at earlier stages in the load planning and building process. Access to a list of equipment sizes and types is optionally provided to the system user by accessing the Equipment Profile 70.).
Gabrielson teaches:
Claim 6. The method of claim 5, further comprising: determining that a chassis belonging to a first chassis pool to which a first customer belongs is not available to receive a container belonging to the first customer (¶0039 The Booking Queue Profile 74 includes booking information relating to inland freight shipments that the Large Retail Entity (LRE) is responsible for building into container loads. This list of shipments is also described as the booking queue. The booking information, such as quantities, types of goods, whether loads are Container Yard (CY) loads vs. Container Freight Station (CFS) loads, as well as whether the large retail entity is responsible for shipping to port (FCA) or the vendor is responsible for shipping to port (FOB), and other booking information is a result of one or more vendor booking processes used by the Large Retail Entity (LRE). Although FCA and FOB are used as examples herein, it should be understood that use of other types of shipping information and designators, including all of those associated with internationally recognized Incoterms, are contemplated.).
Gabrielson teaches:
Claim 7. The method of claim 6, wherein synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon includes: recommending a mismount of the container belonging to the first customer to a chassis belonging to a second chassis pool to which the first customer does not belong (¶0040 The Load Planning Component 42 utilizes information from the Profile Maintenance Component 40 to help field consolidate inland freight shipments into container loads using multi-stop routes (as opposed to consolidating inland freight shipments at container freight stations, for example). Generally speaking, and where appropriate, the container loads are planned to reduce trips to port, to generate fuller container loads, and/or to address the need for alternative use containers to meet special shipment needs (e.g., reefers). Some embodiments also promote utilization of larger containers where appropriate. For example, one container planning hierarchy includes, 45 foot container loads first, then 40 foot high cube container loads, then 40 foot standard container loads, and so forth, although other hierarchies are also contemplated.).
Gabrielson teaches:
Claim 8. The method of claim 7, wherein recommending the mismount is in response to one or more of: a determination that the chassis belonging to the second chassis pool to which the first customer does not belong is not needed to receive a container belonging to a second customer that belongs to the second chassis pool before the end of the planning horizon; a determination that the container belonging to the first customer is to be removed from the chassis belonging to the second chassis pool to which the first customer does not belong when the chassis belonging to the first chassis pool to which the first customer belongs becomes available (¶0040 The Load Planning Component 42 utilizes information from the Profile Maintenance Component 40 to help field consolidate inland freight shipments into container loads using multi-stop routes (as opposed to consolidating inland freight shipments at container freight stations, for example). Generally speaking, and where appropriate, the container loads are planned to reduce trips to port, to generate fuller container loads, and/or to address the need for alternative use containers to meet special shipment needs (e.g., reefers). Some embodiments also promote utilization of larger containers where appropriate. For example, one container planning hierarchy includes, 45 foot container loads first, then 40 foot high cube container loads, then 40 foot standard container loads, and so forth, although other hierarchies are also contemplated.).
Gabrielson teaches:
Claim 9. The method of claim 6, wherein synchronizing, based on the unit traffic prediction and the one or more capacity constraints associated with the chassis resource capacity of the hub over the planning horizon, the consolidation operational stream and the deconsolidation operational stream over a planning horizon includes: recommending placing the container belonging to the first customer in a stacking parking lot until the chassis belonging to the first chassis pool to which the first customer belongs becomes available (¶0029 The Inland Planning Zone Profile 60 includes planning zone information. FIG. 3 is a schematic illustration showing a plurality of vendor supply locations 80 (e.g., factories) associated to a plurality of ports of origin, or ports 82, according to one or more planning zones 84. The planning zones 84 are generated using geographic boundaries, governmental boundaries (e.g., state boundaries, province boundaries, city boundaries, or the like), and latitudinal and longitudinal coordinates relative to the vendor supply locations 80. The planning zones are also generated in view of customs district boundaries or are otherwise customs-district-based zones.).
As per claims 10-18 and 19,20, the system and computer-based tool tracks the method of claims 1-9 and 1,7, respectively, resulting in substantially similar limitations. The same cited prior art and rationale of claims 1-9 and 1,7 are applied to claims 11-18 AND 19,20, respectively. Gabrielson discloses that the embodiment may be found as a system and computer-based tool (Figs. 1-2 and ¶0023).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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/KURTIS GILLS/Primary Examiner, Art Unit 3624
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