DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-11 were previously pending and subject to a non-final rejection dated April 7, 2025. In Response, submitted September 7, 2025, claims 1, 3, 5, 6, 10, and 11 were amended, and claims 12-15 were added. No new subject matter was introduced by these amendments. Therefore, claims 1-15 are currently pending and subject to the following final rejection.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on March 12, 2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s remarks on Pages 7-10 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 101, have been fully considered and are not found persuasive.
On Pages 8-9 of the Response, Applicant argues “Applicant respectfully submits that claim 1 is patent eligible under Prong Two of the revised Step 2A of the Alice test. … Without any admissions and solely in an effort to expedite prosecution of the present application, independent claim 1 is amended to recite ‘instructions to a quantum computer to execute an optimization process to optimize the delivery plan for the extracted delivery request for each delivery condition, the optimization process comprising identifying a set of variables that minimize a Hamiltonian expression.’ Applicant respectfully submits issuing instructions to a quantum computer to perform a process that includes identifying a set of variables that minimize a Hamiltonian expression is not a fundamental economic principle or practice, is not a commercial or legal interaction, and does not manage personal behavior or relationships or interactions between people. Therefore, these features cannot be categorized as certain methods of organizing human activity. Further, these features are also not directed to mathematical concepts or mental processes.”
Examiner notes, as discussed further in the detailed rejection below, though “instructions … to execute an optimization process to optimize the delivery plan for the extracted delivery request for each delivery condition, the optimization process comprising identifying a set of variables that minimize a[n] … expression” is not intrinsically “a certain method of organizing human activity”, or more specifically a commercial interaction, however when viewed within the context of the full recitation of the abstract idea (for example, that the instructions and optimization process purposes are to “output the optimized delivery plan for each delivery condition” See claim 1), it becomes very clear that the abstract idea as a whole recites “certain methods of organizing human activity”. Further, the presence of additional elements such as “a quantum computer” and “a Hamiltonian expression” do not preclude the claims from reciting an abstract idea. Further still, Examiner notes that elements of the recited abstract idea, such as “identifying a set of variables that minimize a[n] … expression” may also be properly classified within the abstract idea grouping of “mathematical concepts”, however for the sake of clarity and to prevent confusion only the single grouping which most fully captures the recited abstract idea is noted within the detailed rejection.
On Page 9 of the Response, Applicant argues “Moreover, Applicant respectfully submits these features integrate any alleged abstract idea into a practical application. Specifically, paragraph [0049] of the specification indicates a quantum computer includes ‘additional elements different from the usual elements of a general- purpose computer,’ and that use of a quantum computer for obtaining parameters of a Hamiltonian express is ‘an improvement in optimization processing.’ In this regard, these additional features integrate any alleged abstract idea into a practical application. Accordingly, amended claim 1 integrates any possible judicial exception into a practical application, and accordingly is patent eligible under Prong Two of the revised Step 2A of the Alice test.
Examiner notes, as will be discussed further in the detailed rejection below, while the “quantum computer” is not a “general-purpose computer” it still fails to integrate the abstract idea into a practical application. The quantum computer, and further the Hamiltonian expression, are described at such a high levels of generality within the specification, that they merely serve to generally link the performance of the abstract idea to the field of quantum computing. Though the argument alleges that use of these additional elements results in “an improvement in optimization processing”, the additional elements themselves are not improved, nor is the broader technology of quantum computing. In the instant case, the improvement is found only in the abstract idea of “optimization processing”, that is processes for optimizing data, and it is important to keep in mind that an improvement in the abstract idea itself .is not an improvement in technology. See MPEP 2106.05(a)(II).
On Pages 9-10 of the Response, Applicant argues “Moreover, Applicant respectfully submits that even if it is assumed the claim is directed to an abstract idea, which is not conceded, independent claim 1 recites significantly more than any allegedly abstract idea. … As discussed below, the cited art does not teach or suggest the features of independent claim 1. Therefore, claim 1 provides an ‘inventive concept,’ and does not simply append well- understood, routine or conventional activities. Accordingly, independent claim 1 recites significantly more than any allegedly abstract idea. …As discussed above, independent claim 1 does not recite an abstract idea, integrates any alleged abstract idea into a practical application, and recites significantly more than any alleged abstract idea. Thus, it is clear independent claim 1 is directed to patent eligible subject matter. To the extent independent claims 10 and 11 recite features similar to those discussed above with respect to independent claim 1, Applicant respectfully submits independent claims 10 and 11 are directed to patent eligible subject matter for at least reasons similar to those discussed above with respect to independent claim 1. Additionally, Applicant respectfully submits that claims 2-9 recite patent eligible subject matter for at least the reasons discussed above due to their respective dependencies.
Examiner notes, “well understood, routine, and conventional” is merely a single test used to determine eligibility at Step 2B. As discussed further in the detailed rejection, which reflects the analysis of previous office actions, the rejection of these claims does not rely on “well understood, routine, and conventional” but rather rejects the claims as ineligible on the basis of the additional elements amounting to merely “apply it” or generally linking the abstract idea to a technical field. Further, “Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination. See Mayo, 566 U.S. at 91, 101 USPQ2d at 1973 (rejecting “the Government’s invitation to substitute §§ 102, 103, and 112 inquiries for the better established inquiry under § 101”). As made clear by the courts, the ‘“novelty” of any element or steps in a process, or even of the process itself, is of no relevance in determining whether the subject matter of a claim falls within the § 101 categories of possibly patentable subject matter.’ Intellectual Ventures I v. Symantec Corp., 838 F.3d 1307, 1315, 120 USPQ2d 1353, 1358 (Fed. Cir. 2016) (quoting Diamond v. Diehr, 450 U.S. at 188–89, 209 USPQ at 9).” See MPEP 2106.05(I). Therefore, after full and proper analysis the claims remain ineligible over 101 and stand rejected.
Applicant’s remarks on Pages 11-13 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 103, have been fully considered but are moot in light of the amended claims.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 12 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 12 recites “further comprising the quantum computer” with no further limitations given. The “quantum computer” is already recited in claim 1 limitation 5, therefore claim 12 fails to further narrow the limitations of claim 1. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-9 and 12-15 are directed to a system (i.e., a machine); claim 10 is directed to a method (i.e., a process); and claim 11 is directed to a non-transitory computer readable information recording medium (i.e., a machine). Therefore, claims 1-15 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One
Independent claims 1, 10 and 11 substantially recite accepting input of an additional delivery request including a specification of multiple delivery conditions;
extracting a delivery request corresponding to the input delivery conditions, including the additional delivery request;
generating a delivery plan for each delivery condition by issuing instructions to execute an optimization process to optimize the delivery plan for the extracted delivery request for each delivery condition, the optimization process comprising identifying a set of variables that minimize an expression; and
outputting the optimized delivery plan for each delivery condition.
The limitations stated above are processes/functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial or legal interactions) of “creating delivery plans” (Specification, Para. 1). Therefore, the claim recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1, 10, and 11 as a whole amount to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent). The claim recites the additional elements of: (i) a memory storing instructions (claim 1), (ii) one or more processors configured to execute the instructions (claim 1), (iii) a quantum computer (claims 1, 10, 11), and (iv) a Hamiltonian expression (claims 1, 10, 11).
The additional elements of (i) a memory storing instructions, (ii) one or more processors configured to execute the instructions are recited at a high level of generality (see [0097] of the Applicant’s Specification discussing the memory storing instructions, and [0064] discussing the one or more processors configured to execute the instructions) such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
The additional element of (iii) a quantum computer, and (iv) a Hamiltonian expression are recited at a high level of generality (See [0034] of the Applicant's PG Publication discussing the quantum computer, and [0035 & 0050] discussing the Hamiltonian expression) such that when viewed as whole/ordered combination, do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., quantum computing) (See MPEP 2106.05(h)).
Accordingly, these additional elements, when viewed as a whole/ordered combination [See Figures 3 and 11 showing all the additional (i) a memory storing instructions, (ii) one or more processors configured to execute the instructions, (iii) a quantum computer, and (iv) a Hamiltonian expression in combination], do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claims 1, 10, and 11 are ineligible.
Dependent Claims 2 and 4-9 merely narrow the previously recited abstract idea limitations. For reasons described above with respect to claim 1 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 2 and 4-9 are also ineligible.
Step 2A, Prong Two
Dependent Claim 3 further narrow the previously recited abstract idea limitations reciting the abstract idea of “generating an objective function used for optimization; and sending the generated objective function to execute the optimization processing”. Claim 3 also recites the additional elements of an Ising model and an annealing machine, which is recited at a high-level of generality (See [0035 & 0048] of the Applicant’s Specification disclosing the Ising model, [0034] disclosing the annealing machine) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e. function optimization and quantum computing solvers) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements of an Ising model and an annealing machine do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 3 is ineligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3, 5, 7, 10-12, 14 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Falcone (US 20140330738) (hereafter Falcone) in view of Miyahara (US 20230065108) (hereafter Miyahara).
In regards to claim 1, Falcone discloses a delivery plan creation system comprising: a memory storing instructions; and one or more processors configured to execute the instructions to: accept input of an additional delivery request including a specification of multiple delivery conditions; (Para. 25, 31-32, 49) (“The food delivery truck is also capable of operating in a temporary fixed location. It will be understood that the invention is not limited to this example embodiment and that other delivery services, such as other food delivery and package delivery services, may also use the techniques disclosed herein.” “The intelligent delivery platform (i.e. a delivery plan creation system) is continuously operating in the background to receive customer requests, schedule as many requested delivery times as possible … the platform optimizes the operator's financial performance … The platform accepts customer order information, such as contact information, delivery location, and requested delivery time (i.e. accept input of an additional delivery request including a specification of multiple delivery conditions)” “a system (i.e. a delivery plan creation system) 100 for providing an automated optimization … the components, such as processor 101 and memory 104 are in a fixed location, such as on a server 105.”)
Falcone discloses extract a delivery request corresponding to the input delivery conditions, including the additional delivery request; (Para. 32) (“The customer ordering process is automated and, therefore, the customer may order at any time. The platform accepts customer order information (i.e. extract a extract a delivery request corresponding to the input delivery conditions), such as contact information, delivery location, and requested delivery time (i.e. including the additional delivery request).”)
Falcone discloses generate a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request (Para. 66, 121, 124) (“The automated optimization/collaboration application works to fill openings in schedule 400 during the evening residential period 302 in order to optimize usage … the automated optimization/collaboration application generates sufficient new business and coordinates new customer orders so that the delivery truck drives from one destination to another stopping only long enough to make a delivery with minimal dead time waiting to start the next order/delivery” “Dynamic route optimizer module 1315 works with the interactive scheduler module 1312 to create an initial baseline route plan. The dynamic route optimizer module 1315 also provides updates to the route plan (i.e. by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request) to serve additional customer requests (i.e. generate a delivery plan for the extracted delivery request).” “The integrated delivery platform 1301 further includes software code or module for optimization business logic and rules”)
Falcone discloses output the optimized delivery plan. (Para. 125) (“Overall, the process treats every minute wasted as a lost business opportunity and, therefore, is designed to provide route optimization (i.e. output the optimized delivery plan)”)
As discussed above, Falcone discloses generate a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses the generate a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request of Falcone is generate a delivery plan of Falcone for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone, the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression; and (Para. 11, 12, 123, 128) (“input of a delivery planning problem for generating, under predetermined constraint conditions, a plan for delivering … an optimization function generation unit that generates an optimization function for variables representing quantum states for solving the delivery planning problem by using the input (i.e. generate a delivery plan for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan).” “generate an optimization function for variables representing quantum states for solving a delivery planning problem (i.e. generate a delivery plan of Falcone for each delivery condition) with predetermined constraint conditions (i.e. an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone).” “an Ising Hamiltonian using spins may be employed for the optimization function. Here, the spins are variables expressing quantum states” “the Ising Hamiltonian, which is an optimization function, is a function designed to have a minimum value only when all of the first to sixth constraint conditions are satisfied (i.e., the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression).”)
As discussed above, Falcone discloses output the optimized delivery plan. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses output the optimized delivery plan of Falcone is for each delivery condition of Falcone. (Para. 61-63, 123) (“Quantum bits used to solve the delivery planning problem will be described. Here, the quantum bits are variables expressing quantum states having a value of 1 or 0. In the delivery planning problem according to the present invention, six types of quantum bits, carStop.sub.t, c, p, carMove.sub.t, c, staffStop.sub.t, s, p, staffMove.sub.t, s, ride.sub.t, s, c, and noRide.sub.t, s, are defined and used as described … With these definitions, the constraint … is satisfied (i.e. output the optimized delivery plan of Falcone is for each delivery condition of Falcone).” “instead of using the QUBO objective function using quantum bits, an Ising Hamiltonian using spins may be employed for the optimization function.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 3, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses wherein the processor is configured to execute the instructions to: generate an objective function used for optimization by a by the Hamiltonian expression or an Ising model; and send the generated objective function to a to the quantum computer or an annealing machine to execute optimization processing. (Para 12, 113, 123) (“generate an optimization function for variables representing quantum states for solving a delivery planning problem with predetermined constraint conditions.” “Thus, the QUBO objective function CarSharing is a function in which a solution can be achieved by a quantum annealing machine or an Ising machine.” “Instead of using the QUBO objective function using quantum bits, an Ising Hamiltonian using spins may be employed for the optimization function.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 5, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses wherein the processor is configured to execute the instructions to optimize the delivery plan by minimizing an objective function defining cost required for delivery. (Claim 1) (“a plan for delivering …, so as to satisfy a condition for minimizing a total of a staff cost and a vehicle cost incurred until the delivery end time”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 7, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone discloses wherein the processor is configured to execute the instructions to: accept input of the additional delivery request including a specification of multiple delivery times as the delivery conditions; (Para. 32) (“The platform accepts customer order information, such as contact information, delivery location, and requested delivery time. The customer identifies a preferred delivery time, which could be … a range of times”)
Flacone discloses extract the delivery request scheduled for the specified delivery times, including the additional delivery request; (Para. 33) (“The platform decides which customer requests to confirm and which customer requests to negotiate. For confirmed requests, the platform sends out customer commitment time notifications. Once the request has been confirmed, the operator has guaranteed that the delivery will be made at the requested time.” That is, delivery requests are extracted for each request including the additional delivery request.)
Falcone discloses optimize the delivery plan for the extracted delivery request for each specified delivery time; and (Para. 32, 121) (“By compiling all relevant order information, the platform will build a baseline route plan that is optimized to minimize windshield time between deliveries while meeting requested delivery times” “Dynamic route optimizer module 1315 works with the interactive scheduler module 1312 to create an initial baseline route plan. The dynamic route optimizer module 1315 also provides updates to the route plan to serve additional customer requests (i.e. optimize a delivery plan for the extracted delivery request).”)
Falcone discloses output results optimized for each delivery time. (Para. 125) (“Overall, the process treats every minute wasted as a lost business opportunity and, therefore, is designed to provide route optimization”)
In regards to claim 10, Falcone discloses a delivery plan creation method by a computer comprising: accepting input of an additional delivery request including a specification of multiple delivery conditions; (Para. 25, 31-32, 99) (“The food delivery truck is also capable of operating in a temporary fixed location. It will be understood that the invention is not limited to this example embodiment and that other delivery services, such as other food delivery and package delivery services, may also use the techniques disclosed herein.” “The intelligent delivery platform (i.e. a delivery plan creation method by a system) is continuously operating in the background to receive customer requests, schedule as many requested delivery times as possible … the platform optimizes the operator's financial performance … The platform accepts customer order information, such as contact information, delivery location, and requested delivery time (i.e. accepting input of an additional delivery request including a specification of multiple delivery conditions)” “a flowchart of a method for optimizing a delivery schedule”)
Falcone discloses extracting a delivery request corresponding to the input delivery conditions, including the additional delivery request; (Para. 32) (“The customer ordering process is automated and, therefore, the customer may order at any time. The platform accepts customer order information (i.e. extracting a extract a delivery request corresponding to the input delivery conditions), such as contact information, delivery location, and requested delivery time (i.e. including the additional delivery request).”)
Falcone discloses generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request (Para. 66, 121, 124) (“The automated optimization/collaboration application works to fill openings in schedule 400 during the evening residential period 302 in order to optimize usage … the automated optimization/collaboration application generates sufficient new business and coordinates new customer orders so that the delivery truck drives from one destination to another stopping only long enough to make a delivery with minimal dead time waiting to start the next order/delivery” “Dynamic route optimizer module 1315 works with the interactive scheduler module 1312 to create an initial baseline route plan. The dynamic route optimizer module 1315 also provides updates to the route plan (i.e. by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request) to serve additional customer requests (i.e. generate a delivery plan for the extracted delivery request).” “The integrated delivery platform 1301 further includes software code or module for optimization business logic and rules”)
Falcone discloses outputting the optimized delivery plan. (Para. 125) (“Overall, the process treats every minute wasted as a lost business opportunity and, therefore, is designed to provide route optimization (i.e. output the optimized delivery plan)”)
As discussed above, Falcone discloses generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses the generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request of Falcone is generating a delivery plan of Falcone for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone, the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression; and (Para. 11, 12, 123, 128) (“input of a delivery planning problem for generating, under predetermined constraint conditions, a plan for delivering … an optimization function generation unit that generates an optimization function for variables representing quantum states for solving the delivery planning problem by using the input (i.e. generate a delivery plan for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan).” “generate an optimization function for variables representing quantum states for solving a delivery planning problem (i.e. generate a delivery plan of Falcone for each delivery condition) with predetermined constraint conditions (i.e. an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone).” “an Ising Hamiltonian using spins may be employed for the optimization function. Here, the spins are variables expressing quantum states” “the Ising Hamiltonian, which is an optimization function, is a function designed to have a minimum value only when all of the first to sixth constraint conditions are satisfied (i.e., the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression).”)
As discussed above, Falcone discloses outputting the optimized delivery plan. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses outputting the optimized delivery plan of Falcone is for each delivery condition of Falcone. (Para. 61-63, 123) (“Quantum bits used to solve the delivery planning problem will be described. Here, the quantum bits are variables expressing quantum states having a value of 1 or 0. In the delivery planning problem according to the present invention, six types of quantum bits, carStop.sub.t, c, p, carMove.sub.t, c, staffStop.sub.t, s, p, staffMove.sub.t, s, ride.sub.t, s, c, and noRide.sub.t, s, are defined and used as described … With these definitions, the constraint … is satisfied (i.e. output the optimized delivery plan of Falcone is for each delivery condition of Falcone).” “instead of using the QUBO objective function using quantum bits, an Ising Hamiltonian using spins may be employed for the optimization function.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 11, Falcone discloses a non-transitory computer readable information recording medium storing a delivery plan creation program, when executed by a processor, that performs a method for: accepting input of an additional delivery request including a specification of multiple delivery conditions; (Para. 25, 31-32, 49) (“The food delivery truck is also capable of operating in a temporary fixed location. It will be understood that the invention is not limited to this example embodiment and that other delivery services, such as other food delivery and package delivery services, may also use the techniques disclosed herein.” “The intelligent delivery platform (i.e. a delivery plan creation method by a system) is continuously operating in the background to receive customer requests, schedule as many requested delivery times as possible … the platform optimizes the operator's financial performance … The platform accepts customer order information, such as contact information, delivery location, and requested delivery time (i.e. accepting input of an additional delivery request including a specification of multiple delivery conditions)” “Software code and other data that is required by the automated optimization/collaboration application are stored in a database or memory 104, which may be any form of volatile or non-volatile electronic storage, such as a hard drive, cache, RAM, ROM, or flash memory. In some embodiments, the components, such as processor 101 and memory 104 are in a fixed location, such as on a server 105 (i.e. a non-transitory computer readable information recording medium storing a delivery plan creation program, when executed by a processor, that performs a method).”)
Falcone discloses extracting a delivery request corresponding to the input delivery conditions, including the additional delivery request; (Para. 32) (“The customer ordering process is automated and, therefore, the customer may order at any time. The platform accepts customer order information (i.e. extracting a extract a delivery request corresponding to the input delivery conditions), such as contact information, delivery location, and requested delivery time (i.e. including the additional delivery request).”)
Falcone discloses generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request (Para. 66, 121, 124) (“The automated optimization/collaboration application works to fill openings in schedule 400 during the evening residential period 302 in order to optimize usage … the automated optimization/collaboration application generates sufficient new business and coordinates new customer orders so that the delivery truck drives from one destination to another stopping only long enough to make a delivery with minimal dead time waiting to start the next order/delivery” “Dynamic route optimizer module 1315 works with the interactive scheduler module 1312 to create an initial baseline route plan. The dynamic route optimizer module 1315 also provides updates to the route plan (i.e. by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request) to serve additional customer requests (i.e. generate a delivery plan for the extracted delivery request).” “The integrated delivery platform 1301 further includes software code or module for optimization business logic and rules”)
Falcone discloses outputting the optimized delivery plan. (Para. 125) (“Overall, the process treats every minute wasted as a lost business opportunity and, therefore, is designed to provide route optimization (i.e. output the optimized delivery plan)”)
As discussed above, Falcone discloses generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses the generating a delivery plan by execut[ing] an optimization process to optimize the delivery plan for the extracted delivery request of Falcone is generating a delivery plan of Falcone for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone, the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression; and (Para. 11, 12, 123, 128) (“input of a delivery planning problem for generating, under predetermined constraint conditions, a plan for delivering … an optimization function generation unit that generates an optimization function for variables representing quantum states for solving the delivery planning problem by using the input (i.e. generate a delivery plan for each delivery condition by issuing instructions to a quantum computer to execute an optimization process to optimize the delivery plan).” “generate an optimization function for variables representing quantum states for solving a delivery planning problem (i.e. generate a delivery plan of Falcone for each delivery condition) with predetermined constraint conditions (i.e. an optimization process to optimize the delivery plan for the extracted delivery request of Falcone for each delivery condition of Falcone).” “an Ising Hamiltonian using spins may be employed for the optimization function. Here, the spins are variables expressing quantum states” “the Ising Hamiltonian, which is an optimization function, is a function designed to have a minimum value only when all of the first to sixth constraint conditions are satisfied (i.e., the optimization process of Falcone comprising identifying a set of variables that minimize a Hamiltonian expression).”)
As discussed above, Falcone discloses outputting the optimized delivery plan. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses outputting the optimized delivery plan of Falcone is for each delivery condition of Falcone. (Para. 61-63, 123) (“Quantum bits used to solve the delivery planning problem will be described. Here, the quantum bits are variables expressing quantum states having a value of 1 or 0. In the delivery planning problem according to the present invention, six types of quantum bits, carStop.sub.t, c, p, carMove.sub.t, c, staffStop.sub.t, s, p, staffMove.sub.t, s, ride.sub.t, s, c, and noRide.sub.t, s, are defined and used as described … With these definitions, the constraint … is satisfied (i.e. output the optimized delivery plan of Falcone is for each delivery condition of Falcone).” “instead of using the QUBO objective function using quantum bits, an Ising Hamiltonian using spins may be employed for the optimization function.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 12, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses further comprising the quantum computer. (Para. 1) (“generating an optimization function for solving a combinatorial optimization problem by a quantum computer.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 14, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses wherein the optimization process comprises optimizing the delivery plan for each delivery condition in parallel.. (Para. 135) (“The processing described in the embodiments is not only executed in time series in the described order, but also may be executed in parallel”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
In regards to claim 15, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses wherein the processor is configured to execute the instructions to: generate an objective function used for optimization by the Hamiltonian expression; and (Para. 123, 128) (“an Ising Hamiltonian using spins may be employed for the optimization function.” “the Ising Hamiltonian, which is an optimization function, is a function designed to have a minimum value only when all of the first to sixth constraint conditions are satisfied”)
Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses send the generated objective function to the quantum computer to execute optimization processing, (Para. 128-129) (“he Ising Hamiltonian, which is an optimization function, is a function designed to have a minimum value only when all of the first to sixth constraint conditions are satisfied. The optimization function output by the optimization function generation apparatus 100 is input to a quantum annealing machine”)
Falcone does not explicitly disclose, however Miyahara, in the same field of endeavor, discloses wherein the objective function is represented as a function that adds cost terms and penalty terms. (Para. 77, 120) (“Restriction is an expression representing a condition other than a minimization condition, Cost is an expression representing the minimization condition, and Penalty is a constant representing a weight of the expression Restriction.” “the function Cost representing the optimization condition is a function defined so that a value thereof is smaller when the total of the staff cost and the vehicle cost incurred until the delivery end time”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone with the plan optimization of Miyahara in order to improve the system’s ability to more efficiently solve combinatorial optimizations. (Miyahara – Para. 2)
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Falcone in view of Miyahara and further in view of Lindbo (US 20170323250) (hereafter Lindbo).
In regards to claim 2, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone in view of Miyahara does not explicitly disclose, however Lindbo, in the same field of endeavor, discloses wherein the processor is configured to execute the instructions to: predict a delivery request expected to be made in the future corresponding to the input delivery conditions; (Para. 122-123) (“The future state prediction subsystem 414 may be configured for developing predictions on anticipated logistical factors that may impact logistical decision-making. For example, anticipated orders, capacity, labour, customer demand, traffic patterns, etc. may be considered. The fulfillment optimisation subsystem 410 may utilise the predictions in optimizing … the future state prediction subsystem 414 may be configured to consider various probabilities and/or dependencies. For example, the probabilities for different resources to be needed at different points in time may be considered. As customer orders arrive, or not, as may occur, these probabilities may change. During various stages of the optimisation process, the system may be configured to dynamically change one or more variables and/or parameters, though, for example, scheduling more or less labour or more or fewer delivery vehicles, for example. Accordingly, the related probabilities may be subject to change.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone in view of Miyahara with the predictions of Lindbo in order to allow the system to “improve one or more parameters associated with the fulfillment of orders”. (Lindbo – Para. 8)
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Falcone in view of Miyahara and further in view of Williams (US 20020198794) (hereafter Williams).
In regards to claim 4, Falcone in view of Miyahara discloses the limitations of claim 1. Falcone in view of Miyahara does not explicitly disclose, however Williams, in the same field of endeavor, discloses wherein the processor is configured to execute the instructions to output comparative information comparing results optimized for each delivery condition. (Para. 27) (“the objective of the optimization process and to identify various constraints on the optimization process. Thus, the dealer may compare the results for various sets of optimization constraints before deciding on a final objective target that is to be used in the process”
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified delivery optimization of Falcone in view of Miyahara with the predictions of Williams in order to improve overall performance throughout the system. (Williams – Para. 5)
Claim 6 is rejected under 35 U.S.C. 1