DETAILED ACTION
The following is a Final Office Action in response to communications filed September 3, 2026. Claims 1, 4–5, 9–10, 13, 17–18, and 20 are amended. Claims 1–20 are currently pending.
Response to Amendment/Argument
Applicant’s Response is sufficient to overcome the previous rejections of claims 1–20 under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. Accordingly, the previous rejections of claims 1–20 under 35 U.S.C. 112(b) are withdrawn.
With respect to the previous rejections of claims 1–20 under 35 U.S.C. 101, Applicant’s remarks have been fully considered but are not persuasive. Applicant first asserts that the claims embody improvements in simulation technology when considered in view of paragraphs 2–3 of the Specification. Examiner disagrees. Although paragraphs 2–3 of the Specification indicate that current simulation practices face computational and timing problems, the Specification frames the identified problems as mathematical in nature. Specifically, mixed integer linear programming simulations are mathematical simulations, such that the simulation issues identified by Applicant are not technical issues addressed by the additional elements under Step 2A Prong Two or Step 2B. As a result, Applicant’s remarks are not persuasive.
Further, although Applicant indicates that the Specification supports a chain of machine learning elements, the pending claims do not embody a chain of machine learning. As amended, independent claims 1, 10, and 18 obtain deep learning generated simulation inputs. However, the inputs are not generated within the scope of the claims. As a result, the deep learning process is not an additional element for consideration under either Step 2A Prong Two or Step 2B, and Applicant’s remarks are not persuasive.
Finally, Applicant submits that the pending claims are patent-eligible for the same reasons as stated in Ex parte Desjardins. Examiner disagrees. In Ex parte Desjardins, the claims were deemed patent-eligible because the specification identified improvements in machine learning technology. Here, the Specification describes the machine learning operations generically without disclosing any technical improvements. As a result, the pending claims are not analogous to the claims in Ex parte Desjardins, and Applicant’s remarks are not persuasive.
Accordingly, Applicant’s remarks are not persuasive, and the previous rejection is maintained.
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 because the claimed invention is directed to non-statutory subject matter. Specifically, claims 1–20 are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea.
With respect to Step 2A Prong One of the framework, claim 1 recites an abstract idea. Claim 1 includes elements to “receive a network optimization request”; “obtain in-memory initial state target network”; “generate a plurality of in-memory intermediate target networks, wherein each in-memory intermediate target network in the plurality of in-memory intermediate target networks is generated by adding at least one candidate distribution node to the in-memory initial state target network”; “calculate a distorted incremental gain for each in-memory intermediate target network”; and “identify one of the plurality of in-memory intermediate target networks having a highest distorted incremental gain as an optimal iteration target network.”
The limitations above recite an abstract idea. More particularly, the elements above recite certain methods of organizing human activity related to commercial sales activities or behaviors or business relations because the elements describe a process for optimizing a distribution network. Further, the elements to “generate”, “calculate”, and “identify” recite mental processes because the elements embody observations or evaluations that can be practically performed in the mind or by a human using pen and paper. Finally, the element to “calculate” recites mathematical concepts because, when considered in view of Applicant’s Specification, the elements recites mathematical calculations. As a result, claim 1 recites an abstract idea under Step 2A Prong One.
Claims 10 and 18 include substantially similar limitations to those included with respect to claim 1. Further, claim 10 recites “wherein the in-memory initial state target network comprises at least one existing distribution node, at least one demand node, and at least one distribution channel connecting the at least one existing distribution node to the at least one demand node,” and claim 18 recites “wherein the in-memory initial state target network comprises at least one existing distribution node, at least one demand node, and at least one distribution channel connecting the at least one existing distribution node to the at least one demand node” and “wherein the distorted increment gain is determined by a multi-stage optimal fulfillment process”. The identified elements of claims 10 and 18 further recite certain methods of organizing human activity and/or mental processes for the same reasons as stated above. As a result, claims 10 and 18 recite an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claim 1.
Claims 2–9, 11–17, and 19–20 further describe the process for optimizing a distribution network and further recite certain methods of organizing human activity, mental processes, and/or mathematical concepts for the same reasons as stated above. As a result, claims 2–9, 11–17, and 19–20 recite an abstract idea under Step 2A Prong One.
With respect to Step 2A Prong Two of the framework, claim 1 does not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a processor, a non-transitory memory, a machine learning simulation process, and steps to “obtain … inputs”, “execute a machine learning simulation process”, and “store … in the non-transitory memory”. When considered in view of the claim as a whole, the additional elements do not integrate the abstract idea into a practical application because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea; the machine learning simulation process and the step to “execute” do no more than generally link the use of the recited abstract idea to a particular technological environment; and the steps to “obtain” and “store” are insignificant extrasolution activities to the recited abstract idea. As a result, claim 1 does not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
As noted above, claims 10 and 18 include substantially similar limitations to those included with respect to claim 1. Although claim 18 further includes a non-transitory computer readable medium, the additional element, when considered in view of the claim as a whole, does not integrate the abstract idea into a practical application because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea. As a result, claims 10 and 18 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2–9, 11–17, and 19–20 do not include any additional elements beyond those included with respect to the claims from which claims 2–9, 11–17, and 19–20 depend. As a result, claims 2–9, 11–17, and 19–20 do not include any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two for the same reasons as stated above.
With respect to Step 2B of the framework, claim 1 does not include additional elements amounting to significantly more than the abstract idea. As noted above, claim 1 includes additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements include a processor, a non-transitory memory, a machine learning simulation process, and steps to “obtain … inputs”, “execute a machine learning simulation process”, and “store … in the non-transitory memory”. The additional elements do not amount to significantly more than the recited abstract idea because the additional computer elements are generic computing components that are merely used as a tool to perform the recited abstract idea; the machine learning simulation process and the step to “execute” do no more than generally link the use of the recited abstract idea to a particular technological environment; and the steps to “obtain” and “store” are well-understood, routine, and conventional computer function in view of MPEP 2106.05(d)(II), which identifies receiving data, electronic recordkeeping, and storing and retrieving information in memory as conventional computer functions. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claim 1 does not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
As noted above, claims 10 and 18 include substantially similar limitations to those included with respect to claim 1. Although claim 18 further includes a non-transitory computer-readable medium, the additional element does not amount to significantly more than the recited abstract idea because the additional computer element is a generic computing component that is merely used as a tool to perform the recited abstract idea. Further, looking at the additional elements as an ordered combination adds nothing that is not already present when considering the additional elements individually. As a result, claims 10 and 18 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B.
Claims 2–9, 11–17, and 19–20 do not include any additional elements beyond those included with respect to the claims from which claims 2–9, 11–17, and 19–20 depend. As a result, claims 2–9, 11–17, and 19–20 do not include any additional elements that amount to significantly more than the recited abstract idea under Step 2B for the same reasons as stated above.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1–20 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Allowable Subject Matter
Claims 1–20 are allowable over the prior art of record. More particularly, when considered in combination with the remaining claim elements, the prior art references of record, as discussed below, do not disclose the combination of elements to “generate a plurality of in-memory intermediate target networks, wherein each in-memory intermediate target network in the plurality of in-memory intermediate target networks is generated by adding at least one candidate distribution node to the in-memory initial state target network” and “calculate, based on the simulated operation of each in-memory intermediate target network, a distorted incremental gain for each in-memory intermediate target network,” as recited in independent claims 1, 10, and 18.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM S BROCKINGTON III whose telephone number is (571)270-3400. The examiner can normally be reached M-F, 8am-5pm, EST.
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/WILLIAM S BROCKINGTON III/Primary Examiner, Art Unit 3623
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