DETAILED ACTION
This office action is made final. Claims 1-20 are pending. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Applicant’s amendment date 09/02/2026, amended claims 1, 8, and 15.
Response to Amendment
The previously pending rejection to claims 1-20, under 35 USC 101 (Alice), will be maintained.
Response to Arguments
With respect to the 35 USC 103 rejection, Applicant's remarks filed on 02 September 2026 (pages 14-15 in particular) were deemed to be persuasive and adequately reflect the Examiner's opinion as to why claims are allowable over the prior art of record.
With respect to the double patenting, Applicant’s Terminal Disclaimer filed on 09/02/2026 with respect to the Double Patenting rejections has been fully considered and approved.
Further, the reminder of Applicant’s arguments regarding section 35 USC 101 have been fully considered, but they are not persuasive.
Response to Arguments under 35 USC 101:
Applicant asserts that “Step 2A, Prong One - Claim 1 Is Not Directed to a Judicial Exception.” Examiner respectfully disagrees.
Pursuant to 2019 Revised Patent Subject Matter Eligibility Guidance, in order to determine whether a claim is directed to an abstract idea, under Step 2A, we first (1) determine whether the claims recite limitations, individually or in combination, that fall within the enumerated subject matter groupings of abstract ideas (mathematical concepts, certain methods of organizing human activity, or mental processes), and (2) determine whether any additional elements beyond the recited abstract idea, individually and as an ordered combination, integrate the judicial exception into a practical application. 84 Fed. Reg. 52, 54-55. Next, if a claim (1) recites an abstract idea and (2) does not integrate that exception into a practical application, in order to determine whether the claim recites an “inventive concept,” under Step 2B, we then determine whether the claim recites any of the additional elements beyond the recited abstract idea, individually and in combination, are significantly more than the abstract idea itself. 84 Fed. Reg. 56.
Here, under the first prong of Step 2A, the claims (claim 1, and similarly claims 8 and 15) recite “receive an input to a linear programming problem, wherein the linear programming problem comprises a demand planning problem; initialize band optimization parameters, wherein the band optimization parameters comprise a number of bands, and to determine an effective number of bands by, for each pair of consecutive band values, calculating a threshold gap from a Root Mean Square Error and a distance between the band values and, when the gap between the pair of consecutive band values is less than the threshold gap, reducing the number of bands by one, thereby reducing a number of optimization objectives to be solved for the linear programming problem; generate sample intervals using Gibbs sampling from a Gaussian Bayesian Network; normalize and convert the sample intervals to points; update the linear programming problem input based on the points, and solve the updated linear programming problem; calculate KPI values based on the solved linear programming problem; and in response to determining that a stopping criteria is reached, return converged weights indicating optimized KPI values, wherein, when one of the sample intervals drives a calculated KPI value in a desired direction, updates a mean and a covariance of the Gaussian Bayesian Network for a next iteration, the covariance being updated using a shrinking factor that shrinks the covariance to draw a subsequent sample interval in a shrunken search space for the next iteration to achieve faster convergence.” Therefore, contrary to Applicant’s assertions, the claims are directed to mental processes and mathematical calculations.
Applicant asserts that “Step 2A, Prong Two - Claim 1 Integrates Any Alleged Exception into a Practical Application.” Examiner respectfully disagrees.
As discussed above, under the second prong of Step 2A, we determine whether any additional elements beyond the recited abstract idea, individually and as an ordered combination, integrate the judicial exception into a practical application. 84 Fed. Reg. 52, 54-55.
Here, under the second prong of Step 2A, the only additional elements beyond the recited abstract idea of claim 1, and similarly claims 8 and 15, are the recitations of “a computer, comprising a processor and memory, the computer configured to: receive an input to a linear programming problem, wherein the linear programming problem comprises a demand planning problem; initialize band optimization parameters, wherein the band optimization parameters comprise a number of bands, and the computer is further configured to determine an effective number of bands by, for each pair of consecutive band values, calculating a threshold gap from a Root Mean Square Error and a distance between the band values and, when the gap between the pair of consecutive band values is less than the threshold gap, reducing the number of bands by one, thereby reducing a number of optimization objectives to be solved by the computer for the linear programming problem; generate sample intervals using Gibbs sampling from a Gaussian Bayesian Network; normalize and convert the sample intervals to points; update the linear programming problem input based on the points, and solve the updated linear programming problem; calculate KPI values based on the solved linear programming problem; and in response to determining that a stopping criteria is reached, return converged weights indicating optimized KPI values, wherein, when one of the sample intervals drives a calculated KPI value in a desired direction, the computer updates a mean and a covariance of the Gaussian Bayesian Network for a next iteration, the covariance being updated using a shrinking factor that shrinks the covariance to draw a subsequent sample interval in a shrunken search space for the next iteration to achieve faster convergence are carried out by at least one computing device,” and these additional elements, individually and in combination, are nothing more than computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components. Accordingly, contrary to Applicant’s assertions, the judicial exception is not integrated into a practical application under the second prong of Step 2A.
Applicant asserts that “Step 2B - The Claim Elements Amount to Significantly More Than Any Alleged Exception.” Examiner respectfully disagrees.
The MPEP discusses that "the second part of the Alice/Mayo test [(Step 2B)] is often referred to as a search for an inventive concept," and "an 'inventive concept' is furnished by an element or combination of elements that is recited in the claim in addition to (beyond) the judicial exception, and is sufficient to ensure that the claim as a whole amounts to significantly more than the judicial exception itself." MPEP 2106.05 (emphasis added). Further, the MPEP goes on to describe "Step 2B asks: Does the claim recite additional elements that amount to significantly more than the judicial exception? Examiners should answer this question by first identifying whether there are any additional elements (features/limitations/steps) recited in the claim beyond the judicial exception(s), and then evaluating those additional elements individually and in combination to determine whether they contribute an inventive concept (i.e., amount to significantly more than the judicial exception(s)).” MPEP 2106.05 (emphasis added).
The search for an inventive concept under § 101 is distinct from demonstrating novel and non-obviousness. See SAP America Inc. v. Investpic, LLC, No. 2017-2081, slip op. at 2-3 (Fed Cir. May 15, 2018) (citing Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016); Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1315 (Fed. Cir. 2016). Even novel and newly discovered judicial exceptions are still exceptions, despite their novelty. July 2015 Update, p. 3; see SAP America at 2. In Step 2B, “[w]hat is needed is an inventive concept in the non-abstract application realm.” SAP America at 11. As discussed in SAP America, no matter how much of an advance the claims recite, when “the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the non-abstract application realm,” “[a]n advance of that nature is ineligible for patenting.” Id. at 3.
Here, under Step 2B, the only additional elements beyond the recited abstract idea of claim 1, and similarly claims 8 and 15, are the recitations of “a computer, comprising a processor and memory, the computer configured to: receive an input to a linear programming problem, wherein the linear programming problem comprises a demand planning problem; initialize band optimization parameters, wherein the band optimization parameters comprise a number of bands, and the computer is further configured to determine an effective number of bands by, for each pair of consecutive band values, calculating a threshold gap from a Root Mean Square Error and a distance between the band values and, when the gap between the pair of consecutive band values is less than the threshold gap, reducing the number of bands by one, thereby reducing a number of optimization objectives to be solved by the computer for the linear programming problem; generate sample intervals using Gibbs sampling from a Gaussian Bayesian Network; normalize and convert the sample intervals to points; update the linear programming problem input based on the points, and solve the updated linear programming problem; calculate KPI values based on the solved linear programming problem; and in response to determining that a stopping criteria is reached, return converged weights indicating optimized KPI values, wherein, when one of the sample intervals drives a calculated KPI value in a desired direction, the computer updates a mean and a covariance of the Gaussian Bayesian Network for a next iteration, the covariance being updated using a shrinking factor that shrinks the covariance to draw a subsequent sample interval in a shrunken search space for the next iteration to achieve faster convergence are carried out by at least one computing device,” and these additional elements, individually and in combination, are nothing more than computing elements recited at high level of generality implementing the abstract idea on a computer (i.e. apply it), and thus, are no more than applying the abstract idea with generic computer components. Accordingly, contrary to Applicant’s assertions, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B.
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, claims 1 8, and 15 recite an abstract idea. Claims 1 8, and 15 include “receive an input to a linear programming problem, wherein the linear programming problem comprises a demand planning problem; initialize band optimization parameters, wherein the band optimization parameters comprise a number of bands, and determine an effective number of bands by, for each pair of consecutive band values, calculating a threshold gap from a Root Mean Square Error and a distance between the band values and, when the gap between the pair of consecutive band values is less than the threshold gap, reducing the number of bands by one, thereby reducing a number of optimization objectives to be solved for the linear programming problem; generate sample intervals using Gibbs sampling from a Gaussian Bayesian Network; normalize and convert the sample intervals to points; update the linear programming problem input based on the points, and solve the updated linear programming problem; calculate KPI values based on the solved linear programming problem; and in response to determining that a stopping criteria is reached, return converged weights indicating optimized KPI values, wherein, when one of the sample intervals drives a calculated KPI value in a desired direction, updates a mean and a covariance of the Gaussian Bayesian Network for a next iteration, the covariance being updated using a shrinking factor that shrinks the covariance to draw a subsequent sample interval in a shrunken search space for the next iteration to achieve faster convergence”.
The limitations above recite an abstract idea under Step 2A Prong One. More particularly, the elements above recite mental processes-concepts performed in the human mind (including an observation, evaluation, judgment, opinion) and mathematical calculations because the elements describe a process for computing the value of fair share bands. As a result, claims 1 8, and 15 recite an abstract idea under Step 2A Prong One.
Claims 2-7, 9-14, and 16-20 further describe the process for computing the value of fair share bands. As a result, claims 2-7, 9-14, and 16-20 recite an abstract idea under Step 2A Prong One for the same reasons as stated above with respect to claims 1 8, and 15.
With respect to Step 2A Prong Two of the framework, claims 1 8, and 15 do not include additional elements that integrate the abstract idea into a practical application. Claims 1 8, and 15 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements of claims 1 8, and 15 include a computer, a processor, memory, and a non-transitory computer readable medium. 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 computing elements are generic computing elements that are merely used as a tool to perform the recited abstract idea. As a result, claims 1 8, and 15 do not include additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two.
Claims 2-7, 9-14, and 16-20 do not include any additional elements beyond those recited with respect to claims 1 8, and 15. As a result, claims 2-7, 9-14, and 16-20 do not include 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 claims 1 8, and 15.
With respect to Step 2B of the framework, claims 1 8, and 15 do not include additional elements amounting to significantly more than the abstract idea. As noted above, claims 1 8, and 15 include additional elements that do not recite an abstract idea under Step 2A Prong One. The additional elements of claims 1 8, and 15 include a computer, a processor, memory, and a non-transitory computer readable medium. The additional elements do not amount to significantly more than the abstract idea because the additional computing elements are generic computing elements that are 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, independent claims 1 8, and 15 do not include additional elements that amount to significantly more than the abstract idea under Step 2B.
Claims 2-7, 9-14, and 16-20 do not include any additional elements beyond those recited with respect to claims 1 8, and 15. As a result, claims 2-7, 9-14, and 16-20 do not include additional elements that amount to significantly more than the abstract idea under Step 2B for the same reasons as stated above with respect to claims 1 8, and 15.
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.
Conclusion
The prior arts made of record and not relied upon is considered pertinent to applicant's disclosure. Y Gong (Stochastic modelling and analysis of warehouse operations) - 2009 - repub.eur.nl discloses a sample path optimization and perturbation analysis algorithm to search the optimal batch size for a warehousing service provider, and a central finite difference algorithm to search the optimal batch sizes.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAFIZ A KASSIM whose telephone number is (571)272-8534. The examiner can normally be reached 9:00 - 5:00 PM.
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/HAFIZ A KASSIM/Primary Examiner, Art Unit 3623 10/09/2026
