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 .
Claim Objections
Claims 3 and 18 objected to because of the following informalities: Examiner respectfully suggests that “QCM,” recited in the claims as an abbreviation for “constrained quadratic method,” should actually be “CQM.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 15 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 15 recites “the resource allocation data,” but neither claim 15 nor claim 1, upon which claim 15 depends, provides an antecedent basis for this phrase. A person having ordinary skill in the art would be unable to definitely determine which previously recited data was intended to be included by the phrase, and therefore would be unable to determine the metes and bounds of the claim.
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.
For clarity of record, Examiner here notes that claim 13 has been found eligible under 35 U.S.C. 101. Examiner finds that, while claim 12, upon which claim 13 depends, is directed towards an abstract idea and is ineligible, the recitation in claim 13 of the method step, “comprising automatically provisioning one or more of the plurality of computational resources based on the resource allotment data,” integrates the abstract idea into a practical application, for at least the reason that the step effects a particular transformation of the data based on the results generated by the abstract idea (as described in MPEP 2106.05(c)).
Claims 1–12 and 14–28 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Analysis is provided for the claims under the guidelines of MPEP 2106.04(d).
Regarding claim 1:
Step 1:
The claim recites “[a] method comprising” the steps that follow. Thus the claim is to a process, which is a statutory category of invention.
Step 2A prong 1:
The element “an objective function configured to characterize, for a given allotment of the plurality of resources to the plurality of categories, an efficiency of the allotment and an alignment of the allotment with the rankings of the plurality of categories” recites a mathematical operation, namely, a function. The interpretation of the “objective function” of the claim includes a mathematical function.
The element “generating, based on the category data and the resource data, values of one or more constraints associated with” the “objective function” described above recites a mental process. A person could generate constraints based on the category data and the resource data and associated with the objective function, using observation and judgment.
The element (bold only) “generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data, wherein the resource allotment data indicates an allocation of one or more resources of the plurality of resources to one or more categories of the plurality of categories” recites a mental process. A person could generate resource allotment data based on the objective function and the values of the one or more constraints using observation and judgment.
Thus, the claim recites an abstract idea.
Step 2A prong 2:
The elements “receiving category data associated with a plurality of categories and resource data associated with a plurality of resources, wherein: the category data indicates, for each category of the plurality of categories, an amount of resources required by the category, and the resource data indicates, for each resource of the plurality of resources, a ranking of the plurality of categories” recites mere data gathering, which is insignificant extra-solution activity (MPEP 2106.05(g)).
The element (bold only) “generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data” recites the use of a quantum computing system at a high level of generality. No particular design of system or manner of using the system to generate results is described. The element thus merely recites the use of a quantum computer as a tool to perform the abstract idea, and is equivalent to adding the words “apply it” or the equivalent to the judicial exception (MPEP 2106.05(f)).
Thus, the additional elements merely recite the use of a computer as a tool to perform the abstract idea or recite insignificant extra-solution activity. Taken alone, the additional elements do not integrate the abstract idea into a practical application. Considering the elements together as an ordered combination adds nothing that is not present from examining the elements individually. The elements, individually or together, do not describe an improvement in the functioning of technology.
Step 2B:
The claim as a whole does not amount to significantly more than the recited judicial exception.
The element “receiving category data associated with a plurality of categories and resource data associated with a plurality of resources, wherein: the category data indicates, for each category of the plurality of categories, an amount of resources required by the category, and the resource data indicates, for each resource of the plurality of resources, a ranking of the plurality of categories” recites mere data gathering, which is recognized as well-understood, routine, and conventional activity in the art (see MPEP § 2106.05(d)(II)(i)).
The additional element (bold only) “generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data” recites mere instructions to apply the abstract idea.
Even when considered in combination, the additional elements represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 2:
For step 2A prong 1, claim 2 further limits claim 1 and the same elements in claim 2 still recite an abstract idea.
For step 2A prong 2, the further element “wherein the quantum computing system is a quantum annealer” recites the use of a quantum annealer at a high level of generality. No particular design of quantum annealer or method of employing the annealer is described. The element thus merely recites the use of a quantum annealer as a tool to perform the abstract idea, and is equivalent to adding the words “apply it” or the equivalent to the judicial exception (MPEP 2106.05(f)).
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The additional element “wherein the quantum computing system is a quantum annealer” recites mere instructions to apply the abstract idea.
Even when considered in combination, the additional elements represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 3:
For step 2A prong 1, claim 3 further limits claim 2 and the same elements in claim 3 still recite an abstract idea.
The further element “wherein generating the resource allotment data comprises solving a constrained quadradic model (QCM) problem” recites solving a constrained quadradic model, which is a mathematical operation, and which is therefore part of the abstract idea of claim 1.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claim 4:
For step 2A prong 1, claim 4 further limits claim 1 and the same elements in claim 4 still recite an abstract idea.
The further element “wherein generating the resource allotment data comprises minimizing an output value of the objective function” recites objective function minimization at high level of generality. No particular method of minimization is described. Minimizing an objective function is standard in mathematical optimization problems:
“The function f is called, variously, an objective function, criterion function a loss function or cost function minimization,[4] a utility function or fitness function (maximization), or, in certain fields, an energy function or energy functional. A feasible solution that minimizes (or maximizes, if that is the goal) the objective function is called an optimal solution. In mathematics, conventional optimization problems are usually stated in terms of minimization,” Wikipedia, “Mathematical optimization,” entry dated 02/16/2024
Therefore the additional element can be performed as part of the abstract idea of claim 1 and does not serve to integrate the abstract idea into a practical application.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claim 5:
For step 2A prong 1, claim 5 further limits claim 1 and the same elements in claim 5 still recite an abstract idea.
The further element “wherein the one or more constraints associated with the objective function comprise constraints indicating a minimum number of resources of the plurality of resources that should be allocated to each category of the plurality of categories” further limits the mental process identified in claim 1 but the limitation can still be performed as a mental process. A person could determine “constraints indicating a minimum number of resources of the plurality of resources that should be allocated to each category of the plurality of categories” using observation and judgement.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claim 6:
For step 2A prong 1, claim 6 further limits claim 1 and the same elements in claim 6 still recite an abstract idea.
The further element “wherein the values of the constraints indicating a minimum number of resources of the plurality of resources that should be allocated to each category of the plurality of categories are set based on the amount of resources required by each category of the plurality of categories” further limits the mental process identified in claim 1 but the limitation can still be performed as a mental process. A person could determine “constraints indicating a minimum number of resources of the plurality of resources” based on “the amount of resources required by each category of the plurality of categories” using observation and judgement.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claim 7:
For step 2A prong 1, claim 7 further limits claim 1 and the same elements in claim 7 still recite an abstract idea.
The further element “wherein the one or more constraints associated with the objective function comprise constraints indicating a maximum number of categories of the plurality of categories to which each resource of the plurality of resources should be allocated” further limits the mental process identified in claim 1 but the limitation can still be performed as a mental process. A person could determine “constraints indicating a maximum number of categories of the plurality of categories to which each resource of the plurality of resources should be allocated” using observation and judgement.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claim 8:
For step 2A prong 1, claim 8 further limits claim 1 and the same elements in claim 8 still recite an abstract idea.
For step 2A prong 2, the further element “comprising generating a graphical representation of the allocation of the one or more resources” recites outputting results at a high level of generality. No particular output representation or method of generation is described. Thus the element recites mere data output, which is insignificant extra-solution activity (MPEP 2106.05(g)).
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The element “comprising generating a graphical representation of the allocation of the one or more resources” recites mere data output, which is recognized as well-understood, routine, and conventional activity in the art (see MPEP § 2106.05(d)(II)(i)).
Even when considered in combination, the additional elements represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 9:
For step 2A prong 1, claim 9 further limits claim 1 and the same elements in claim 9 still recite an abstract idea.
For step 2A prong 2, the further element “comprising automatically, using a classical computing system, updating one or more databases according to the resource allotment data” recites mere data updating, which is insignificant extra-solution activity (MPEP 2106.05(g)).
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The element “comprising automatically, using a classical computing system, updating one or more databases according to the resource allotment data” recites mere data updating, which is recognized as well-understood, routine, and conventional activity in the art (see MPEP § 2106.05(d)(II)(iv)).
Even when considered in combination, the additional elements represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 10:
For step 2A prong 1, claim 10 further limits claim 1 and the same elements in claim 10 still recite an abstract idea.
For step 2A prong 2, the further element “wherein: the plurality of categories is a plurality of business units, the plurality of resources is a plurality of employees, and the ranking of business units associated with each employee indicates the employee’s preference for working in each business unit” describes the application of the method to a specific problem domain, namely, employees and business units. The element therefore merely connects the abstract idea to a particular field of use, which does not integrate the abstract idea into a practical application.
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The additional element “wherein: the plurality of categories is a plurality of business units, the plurality of resources is a plurality of employees, and the ranking of business units associated with each employee indicates the employee’s preference for working in each business unit” recites a mere field of use to which to apply the abstract idea.
Even when considered in combination, the additional elements connect the abstract idea to a field of use, represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 11:
For step 2A prong 1, claim 11 further limits claim 10 and the same elements in claim 11 still recite an abstract idea.
For step 2A prong 2, the further element “comprising automatically generating and deploying one or more communicative channels for one or more employee devices based on the resource allotment data” recites the communication channels on employee devices at a high level of generality. Therefore the element recites mere data output, which is insignificant extra-solution activity (MPEP 2106.05(g)).
Step 2B:
The claim as a whole does not amount to significantly more than the recited judicial exception.
The element “comprising automatically generating and deploying one or more communicative channels for one or more employee devices based on the resource allotment data” recites mere data transmission, which is recognized as well-understood, routine, and conventional activity in the art (see MPEP § 2106.05(d)(II)(i)).
Even when considered in combination, the additional elements represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 12:
For step 2A prong 1, claim 12 further limits claim 1 and the same elements in claim 12 still recite an abstract idea.
For step 2A prong 2, the further element “wherein: the plurality of categories is a plurality of computational tasks, the plurality of resources is a plurality of computational resources, and the ranking of computational tasks associated with each computational resource indicates an efficiency with which the computational resource could execute each computational task” describes the application of the method to a specific problem domain, namely, computational resources and computational tasks. The element therefore merely connects the abstract idea to a particular field of use, which does not integrate the abstract idea into a practical application.
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The additional element “wherein: the plurality of categories is a plurality of business units, the plurality of resources is a plurality of employees, and the ranking of business units associated with each employee indicates the employee’s preference for working in each business unit” recites a mere field of use to which to apply the abstract idea.
Even when considered in combination, the additional elements connect the abstract idea to a field of use, represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 14:
For step 2A prong 1, claim 14 further limits claim 1 and the same elements in claim 14 still recite an abstract idea.
For step 2A prong 2, the further element “wherein: the plurality of categories is a plurality of land uses, the plurality of resources is a plurality of land plots, and the ranking of land uses associated with each land plot indicates a level of approval for using the land plot for each land use” describes the application of the method to a specific problem domain, namely, land used and land plots. The element therefore merely connects the abstract idea to a particular field of use, which does not integrate the abstract idea into a practical application.
For step 2B, the claim as a whole does not amount to significantly more than the recited judicial exception.
The additional element “wherein: the plurality of categories is a plurality of land uses, the plurality of resources is a plurality of land plots, and the ranking of land uses associated with each land plot indicates a level of approval for using the land plot for each land use” recites a mere field of use to which to apply the abstract idea.
Even when considered in combination, the additional elements connect the abstract idea to a field of use, represent mere instructions to apply the abstract idea to a computer or represent insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible under 35 U.S.C. 101.
Regarding claim 15:
For step 2A prong 1, claim 15 further limits claim 1 and the same elements in claim 15 still recite an abstract idea.
The further element “comprising validating the allocation of the one or more resources based on the resource allocation data, the amounts of resources required by each category, and the rankings of the plurality of categories associated with each resource” recites a mental process. A person could validate an allocation based on “resource allocation data, the amounts of resources required by each category, and the rankings of the plurality of categories associated with each resource” using observation and judgment.
For step 2A prong 2, and step 2B, no further elements remain to be considered. The claim as a whole does not amount to significantly more than the recited judicial exception and is ineligible under 35 U.S.C. 101.
Regarding claims 16–27:
These claims recite “[a] system comprising: a classical computing system; and a quantum computing system, wherein the system is configured to” perform a series of steps. Thus, the claim is to a machine, which is a statutory category of invention. The claims are otherwise analogous to claims 1–10, 12, or 14, respectively, and are ineligible by the same arguments.
Regarding claim 28:
Claim 28 recites “[a] non-transitory computer readable storage medium storing instructions that, when executed by one or more processors of a classical computing system, cause the classical computing system to” perform a series of steps. Thus, the claim is to a manufacture, which is a statutory category of invention. The claim is otherwise analogous to claims 1 and is ineligible by the same arguments.
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.
Claims 1–6, 8–9, 16–21, 23–24, and 28 rejected under 35 U.S.C. 103 over Suzuki et al., US Pre-Grant Publication No. 2020/0327480 (hereafter Suzuki) in view of Yamaguchi et al., US Pre-Grant Publication No. 2026/0105408 (hereafter Yamaguchi).
Regarding claim 1 and analogous claims 16 and 28:
Suzuki teaches:
“A method”: Suzuki, paragraph 0008, “One or more embodiments provide an organization capability evaluation system [method] capable of appropriately evaluating the working capability of a worker and an organization capability evaluation system capable of stabilizing productivity of an organization at a high level”; Suzuki, paragraph 0047, “The working capability calculation unit 55 calculates a working capability for each step (hereinafter, referred to as "step-specific working capability") by executing preset calculation processing on a computer based on the step specific work performance stored in the work record storage unit 53 and the reference working time stored in the evaluation reference storage unit.”
“receiving category data associated with a plurality of categories and resource data associated with a plurality of resources, wherein”: Suzuki, paragraph 0009, “In an aspect (1), an organization capability evaluation system configured to evaluate an organization capability when an organization including a plurality of workers manufactures various products through a plurality of steps, includes a work performance acquisition unit configured to acquire a working time required for work in each of the plurality of steps as a step-specific work performance, an evaluation reference storage unit configured to store a reference working time set for each of the steps as an evaluation reference when evaluating the step-specific work performance, a working capability calculation unit configured to calculate a working capability of each step based on the step-specific work performance and the reference working time, a working capability storage unit configured to store the working capability of each step calculated by the working capability calculation unit as a step-specific working capability, and a step-specific organization capability calculation unit configured to calculate the organization capability for each step based on the step-specific working capability [category data associated with a plurality of categories]”; Suzuki, paragraph 0093, “Further, as shown in FIG. 12, the individual capability calculation unit 61 calculates individual capability data of each worker periodically (for example, every week) by using the individual capability history of each worker stored in the individual capability storage unit 62. For example, the individual capability calculation unit 61 extracts an individual capability history within a predetermined period (for example, three months) for each worker [resource data associated with a plurality of resources].”
“the category data indicates, for each category of the plurality of categories, an amount of resources required by the category, and the resource data indicates, for each resource of the plurality of resources, a ranking of the plurality of categories”: Suzuki, paragraph 0101, “The required skilled workers number storage unit 64 stores the number of skilled workers required in each of the steps P1 to P5 as the required number of skilled workers for each step [category data indicates, for each category of the plurality of categories, an amount of resources required by the category]”; Suzuki, paragraph 0097, “Further, the individual capability calculation unit 61 can also calculate step-specific comprehensive individual capability data and product-specific comprehensive individual capability data for each worker based on the individual capability data [resource data indicates, for each resource of the plurality of resources, a ranking of the plurality of categories]. That is, the individual capability calculation unit 61 can calculate an average of the rank XP1 of the individual capability of the first step P1 in the product X, the rank YP1 of the individual capability of the first step P1 in the product Y, and the rank ZP1 of the individual capability of the first step Pl in the product Z, and set a calculation result as step-specific comprehensive individual capability data OP1 of the first step P1. Further, similarly to the case of the step-specific comprehensive individual capability data OP1 of the first step P1, the individual capability calculation unit 61 can calculate step-specific comprehensive individual capability data OP2 to OPS of the second step P2, the third step P3, the fourth step P4, and the fifth step P5.”
“generating, based on the category data and the resource data, values of one or more constraints associated with an objective function configured to characterize, for a given allotment of the plurality of resources to the plurality of categories, an efficiency of the allotment and an alignment of the allotment with the rankings of the plurality of categories”: Suzuki, paragraph 0099, “The skilled worker extraction unit 63 extracts, for each step and each product, a worker (hereinafter, referred to as ‘skilled worker’) having individual capability being equal to or higher than a predetermined level based on the individual capabilities of the respective workers stored in the individual capability storage unit 62 [an alignment of the allotment with the rankings of the plurality of categories]”; Suzuki, paragraph 0103, “The sufficiency rate calculation unit 65 calculates, based on the number of skilled workers extracted by the skilled worker extraction unit 63 and the required number of skilled workers stored in the required skilled workers number storage unit 64 [values of one or more constraints], a skilled worker sufficiency rate indicating a ratio of the number of skilled workers to the required number of skilled workers. For example, in a case where the required number of skilled workers is 2 in a specific step of a specific product, if the number of extracted skilled workers is 2, the sufficiency rate calculation unit 65 sets a skilled worker sufficiency rate to 100%. In this case, if the number of extracted skilled workers is 1, the skilled worker sufficiency rate is 50%, and if the number of extracted skilled workers is 3, the skilled worker sufficiency rate is 150% [generating … an objective function configured to characterize, for a given allotment of the plurality of resources to the plurality of categories, an efficiency of the allotment and an alignment of the allotment with the rankings of the plurality of categories ].”
(bold only) “and generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data, wherein the resource allotment data indicates an allocation of one or more resources of the plurality of resources to one or more categories of the plurality of categories”: Suzuki, paragraph 0104, “As a result, the organization manager can grasp a step with a low skilled worker sufficiency rate for each product. For example, in a case where there is a step with a low skilled worker sufficiency rate, the manager can increase the number of skilled workers in the step by training a worker who is not a skilled worker among workers having the individual capability of the step. Further, in the case where there is a step with a low skilled worker sufficiency rate, the manager can increase the number of skilled workers in the step by allocating a worker who does not have the individual capability of the step (having no working experience of the step) to the step and training the worker [using the objective function and constraint data to make a decision regarding the allotment of resources to a given category (task), hence, generating, …, based on the objective function and the values of the one or more constraints, resource allotment data, wherein the resource allotment data indicates an allocation of one or more resources of the plurality of resources to one or more categories of the plurality of categories].”
Suzuki does not explicitly teach (bold only) “and generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data.”
Yamaguchi teaches (bold only) “and generating, using a quantum computing system, based on the objective function and the values of the one or more constraints, resource allotment data”: Yamaguchi, paragraph 0008, “The combinatorial optimization device includes a control unit communicably connected to a quantum computer, in which the control unit adds, to a cost
function used for searching for a route when a plurality of vehicles visit a plurality of delivery destinations, a first constraint term for specifying a delivery time and a second constraint term for balancing a workload of each vehicle, and causes the quantum computer to execute quantum computing [using a quantum computing system] for a cost function to which the first constraint term and the second constraint term are added.”
Yamaguchi and Suzuki are analogous arts as they are both related to optimization problems. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the quantum computing of Yamaguchi with the teachings of Suzuki to arrive at the present invention, in order to improve optimization results, as stated in Yamaguchi, paragraph 0012, “According to the present disclosure, it is possible to generate a more realistically available delivery plan using a quantum computer.”
Regarding claim 2 and analogous claim 17:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Yamaguchi further teaches “wherein the quantum computing system is a quantum annealer”: Yamaguchi, paragraph 0025, “Quantum annealing is a method for solving the combinatorial optimization problem by quantum computing. It is expected that a solution to the combinatorial optimization problem can be obtained at a high speed by using quantum annealing.”
Yamaguchi and Suzuki can be combined for the rationale given under claim 1.
Regarding claim 3 and analogous claim 18:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 2.”
Yamaguchi further teaches “wherein generating the resource allotment data comprises solving a constrained quadradic model (QCM) problem”: Yamaguchi, paragraph 0082, “In recent years, a Constrained Quadratic Models (CQM) solver that searches for a solution having a minimum cost from feasible solutions that satisfy all constraints has appeared. The CQM solver searches for a solution that completely satisfies all the constraints. That is, when the CQM solver is used, the quantum computer treats all the constraints as hard constraints. The hard constraint is a constraint condition treated as a constraint required to be satisfied by the quantum computer 40 [generating the resource allotment data comprises solving a constrained quadradic model (QCM) problem].”
Yamaguchi and Suzuki can be combined for the rationale given under claim 1.
Regarding claim 4 and analogous claim 19:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Yamaguchi further teaches “wherein generating the resource allotment data comprises minimizing an output value of the objective function”: Yamaguchi, paragraph 0052, “In the combinatorial optimization using quantum computing, a state of each a that minimizes the Hamiltonian H [minimizing an output value of the objective function], that is, a ground state is searched. Therefore, it is necessary to execute formulation such that an optimal solution to a target problem is in the ground state. An optimization result is obtained by inputting information on the formulated interaction and local magnetic field to a combinatorial optimization algorithm running on a quantum annealing machine or a general-purpose quantum computer.”
Yamaguchi and Suzuki can be combined for the rationale given under claim 1.
Regarding claim 5 and analogous claim 20:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 2.”
Suzuki further teaches “wherein the one or more constraints associated with the objective function comprise constraints indicating a minimum number of resources of the plurality of resources that should be allocated to each category of the plurality of categories”: Suzuki, paragraph 0101, “The required skilled workers number storage unit 64 stores the number of skilled workers required in each of the steps P1 to P5 as the required number of skilled workers for each step [wherein the one or more constraints associated with the objective function comprise constraints indicating a minimum number of resources of the plurality of resources that should be allocated to each category of the plurality of categories]”; Suzuki, paragraph 0103, “The sufficiency rate calculation unit 65 calculates, based on the number of skilled workers extracted by the skilled worker extraction unit 63 and the required number of skilled workers stored in the required skilled workers number storage unit 64, a skilled worker sufficiency rate indicating a ratio of the number of skilled workers to the required number of skilled workers. For example, in a case where the required number of skilled workers is 2 in a specific step of a specific product, if the number of extracted skilled workers is 2, the sufficiency rate calculation unit 65 sets a skilled worker sufficiency rate to 100%. In this case, if the number of extracted skilled workers is 1, the skilled worker sufficiency rate is 50%, and if the number of extracted skilled workers is 3, the skilled worker sufficiency rate is 150%.”
Regarding claim 6 and analogous claim 21:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki further teaches “wherein the values of the constraints indicating a minimum number of
resources of the plurality of resources that should be allocated to each category of the plurality of categories are set based on the amount of resources required by each category of the plurality of categories”: Suzuki, paragraph 0101, “The required skilled workers number storage unit 64 stores the number of skilled workers required in each of the steps Pl to PS as the required number of skilled workers for each step. The organization manager or the like determines the required number of skilled workers of each step for each product, and stores the number in the required skilled workers number storage unit 64 [the values of the constraints indicating a minimum number of
resources of the plurality of resources that should be allocated to each category of the plurality of categories are set based on the amount of resources required by each category of the plurality of categories].”
Regarding claim 8 and analogous claim 23:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki further teaches “comprising generating a graphical representation of the allocation of the one or more resources”: Suzuki, paragraph 0106, “As described above, the organization capability evaluation system 50 includes the display unit 70 that displays calculation results of the organization capability calculation unit 58, the individual capability calculation unit 61, and the sufficiency rate calculation unit 65. For example, the display unit 70 displays the calculation results of the step-specific working capabilities calculated by the step specific organization capability calculation unit 58a on a display device such as a fixed terminal or a mobile terminal that can be used by the organization manager or the like. The display unit 70 can display, on a display device, data indicating transition of the organization capabilities calculated by the organization capability calculation unit 58 [comprising generating a graphical representation of the allocation of the one or more resources].”
Regarding claim 9 and analogous claim 24:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki further teaches “comprising automatically, using a classical computing system, updating one or more databases according to the resource allotment data”: Suzuki, paragraph 0011, “In an aspect (2), an organization capability evaluation system configured to evaluate an organization capability when an organization including a plurality of workers manufactures various products through a plurality of steps, includes a work performance acquisition unit configured to acquire a working time required for work in each of the plurality of steps as a step-specific work performance, an evaluation reference storage unit configured to store a reference working time set for each of the steps as an evaluation reference when evaluating the step-specific work performance, a working capability calculation unit configured to calculate a working capability of each step based on the step-specific work performance and the reference working time, a working capability storage unit configured to store the working capability of each step calculated by the working capability calculation unit as a step-specific working capability [comprising automatically, using a classical computing system, updating one or more databases according to the resource allotment data], and a step-specific organization capability calculation unit configured to calculate the organization capability for each step based on the step-specific working capability.”
Claims 7 and 22 rejected under 35 U.S.C. 103 over Suzuki as modified by Yamaguchi in view of Kang et al., US Pre-Grant Publication No. 2015/0025928 (hereafter Kang).
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki as modified by Yamaguchi does not explicitly teach “wherein the one or more constraints associated with the objective function comprise constraints indicating a maximum number of categories of the plurality of categories to which each resource of the plurality of resources should be allocated.”
Kang teaches “wherein the one or more constraints associated with the objective function comprise constraints indicating a maximum number of categories of the plurality of categories to which each resource of the plurality of resources should be allocated”: Kang, paragraph 0100, “At step 312, allocation constraints for a given employee from the group of employees are specified at a pre-defined time. In an embodiment, the allocation constraints correspond to maximum number of teams to which the given employee from the group of employees can be allocated [wherein the one or more constraints associated with the objective function comprise constraints indicating a maximum number of categories of the plurality of categories to which each resource of the plurality of resources should be allocated].”
Kang and Suzuki are analogous arts as they are both related to resource allocation. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the maximum category allotment for an employee resource of Kang with the teachings of Suzuki to arrive at the present invention, in order to incorporate employee preferences in an allotment, as stated in Kang, 0003, “Further, it is observed that presently the skills and other attributes of employees are gathered manually (for example, via surveys) by the organization. Such approach is very time-consuming and is not able to capture the change in the preference of employees in real-time. Therefore, there is a need for an efficient technique to collect and collate the information about the skills of the group of employees.”
Claims 10–11 and 25 rejected under 35 U.S.C. 103 over Suzuki as modified by Yamaguchi in view of Löffler et al., US Pre-Grant Publication No. 2018/0308029 (hereafter Loffler).
Regarding claim 10 and analogous claim 25:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki as modified by Yamaguchi does not explicitly teach “wherein: the plurality of categories is a plurality of business units, the plurality of resources is a plurality of employees, and the ranking of business units associated with each employee indicates the employee's preference for working in each business unit.”
Loffler teaches “wherein: the plurality of categories is a plurality of business units, the plurality of resources is a plurality of employees, and the ranking of business units associated with each employee indicates the employee's preference for working in each business unit”: As another example, an arrangement for allocating a workspace [the plurality of categories is a plurality of business units] (AP1-AP8) to employees (P) [the plurality of resources is a plurality of employees] in an office building (BG), may comprise: (GMS) a memory unit (SP), in particular of a building management system, wherein infrastructure data (ID) of the office building (BG) are stored in the memory unit (SP); an employee database (MDB) in which work profiles (AP) of the employees (P) are stored, wherein the respective work profiles (AP) comprise activity profiles and comfort preferences of the respective employees [the ranking of business units associated with each employee indicates the employee's preference for working in each business unit] (P); an electronic calendar (EK) in which planned work activities with a start time and end time are stored in each case for a respective employee (P); and a data processing unit (DYE) which is configured to define the allocation of an appropriate workspace (AP1-AP8) for an employee (P) on the basis of the infrastructure data (ID), the respective profile (AP) and the respective planned activities.”
Loffler and Suzuki are analogous arts as they are both related to resource allocation. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the employee preferences of Loffler with the teachings of Suzuki to arrive at the present invention, in order to increase employee satisfaction, as stated in Loffler, paragraph 0005, “The teachings of the present disclosure may be embodied in methods and arrangements for allocating a workspace to employees in an office building, wherein the workspace is appropriate for respective employee preferences and respective work activities.”
Regarding claim 11:
Suzuki as modified by Yamaguchi and Loffler teaches “[t]he method of claim 10.”
Loffler further teaches “comprising automatically generating and deploying one or more communicative channels for one or more employee devices based on the resource allotment data”: Loffler, paragraph 0021, “In some embodiments, the allocation of the appropriate or suitable workspace is communicated to the employee on a mobile communication terminal device (e.g. smartphone ) [comprising automatically generating and deploying one or more communicative channels for one or more employee devices based on the resource allotment data]. An employee is thereby informed in a timely manner of his allocated workspace, e.g. through a notification via a messenger service (e.g. WhatsApp, Twitter). This notification may take place regularly at a predefined time.”
Loffler and Suzuki are combinable for the rationale given under claim 10.
Claims 12–13 and 26 rejected under 35 U.S.C. 103 over Suzuki as modified by Yamaguchi in view of Aurongzeb, US Pre-Grant Publication No. 2022/0283856 (hereafter Aurongzeb).
Regarding claim 12 and analogous claim 26:
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki as modified by Yamaguchi does not explicitly teach “wherein: the plurality of categories is a plurality of computational tasks, the plurality of resources is a plurality of computational resources, and the ranking of computational tasks associated with each computational resource indicates an efficiency with which the computational resource could execute each computational task.”
Aurongzeb teaches “wherein: the plurality of categories is a plurality of computational tasks, the plurality of resources is a plurality of computational resources, and the ranking of computational tasks associated with each computational resource indicates an efficiency with which the computational resource could execute each computational task”: Aurongzeb, paragraph 0004, “Innovative aspects of the subject matter described in this specification may be embodied in a method of minimizing an energy use of virtual machines at one or more information handling systems [the plurality of resources is a plurality of computational resources], including receiving a plurality of computing tasks [plurality of categories is a plurality of computational tasks], each task associated with an energy efficiency indicator; positioning each of the tasks within a task queue indicating an order of execution of the tasks based on the energy efficiency indicator for each task; identifying a plurality of virtual machines, each virtual machine associated with a thermal efficiency indicator based on a historical energy usage of the virtual machine; sorting the virtual machines to identify a distribution of the virtual machines based on the thermal efficiency indicator of the respective virtual machines [the ranking of computational tasks associated with each computational resource indicates an efficiency with which the computational resource could execute each computational]; allocating the virtual machines to execute the tasks based on i) the distribution of the virtual machines and ii) the task queue; and executing the tasks by the virtual machines based on the allocation.”
Aurongzeb and Suzuki are analogous arts as they are both related to resource allocation. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the application of resource application to computing resources of Aurongzeb with the teachings of Suzuki to arrive at the present invention, in order to improve the efficiency of data centers, as stated in Aurongzeb, paragraph 0003, “Worldwide, it's estimated that data centers (server clusters) consume about three percent of the global electric supply and account for about two percent of total greenhouse gas emissions. Increasing the sustainability of such data centers is of great attention.”
Regarding claim 13:
Suzuki as modified by Yamaguchi and Aurongzeb teaches “[t]he method of claim 12.”
Aurongzeb further teaches “comprising automatically provisioning one or more of the plurality of computational resources based on the resource allotment data”: Aurongzeb, paragraph 0004, “Innovative aspects of the subject matter described in this specification may be embodied in a method of minimizing an energy use of virtual machines at one or more information handling systems, including receiving a plurality of computing tasks, each task associated with an energy efficiency indicator; positioning each of the tasks within a task queue indicating an order of execution of the tasks based on the energy efficiency indicator for each task; identifying a plurality of virtual machines, each virtual machine associated with a thermal efficiency indicator based on a historical energy usage of the virtual machine; sorting the virtual machines to identify a distribution of the virtual machines based on the thermal efficiency indicator of the respective virtual machines; allocating the virtual machines to execute the tasks based on i) the distribution of the virtual machines and ii) the task queue; and executing the tasks by the virtual machines based on the allocation [automatically provisioning one or more of the plurality of computational resources based on the resource allotment data].”
Aurongzeb and Suzuki are combinable for the rationale given under claim 12.
Claims 14 and 27 rejected under 35 U.S.C. 103 over Suzuki as modified by Yamaguchi in view of Lichana, US Pre-Grant Publication No. 2004/0117777 (hereafter Lichana).
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki as modified by Yamaguchi does not explicitly teach “wherein: the plurality of categories is a plurality of land uses, the plurality of resources is a plurality of land plots, and the ranking of land uses associated with each land plot indicates a level of approval for using the land plot for each land use.”
Lichana teaches:
“the plurality of categories is a plurality of land uses, the plurality of resources is a plurality of land plots”: Lichana, paragraph 0044, “Land-use is to be understood as: urban/suburban/rural/natural/man-made and use as: as-is or transformed by planning, development and/or management. The methodology is based on a 3D approach to land-use, which combines interactively 1) human, 2) economic, and 3) environmental factors. The combination of land-use data is presented and organized as services in order to offer an array of choices for a quality of life based on qualified and quantified parameters. Data may be broken down in 8 or more sectors: Smart Growth and Sustainable Development; Security; Health Care; Education; Environment; Transportation; Culture and Sports; Information and Communication [the plurality of categories is a plurality of land uses]. Therefore each land-use site [the plurality of resources is a plurality of land plots] may be different both in terms of its make-up and objectives.”
“the ranking of land uses associated with each land plot indicates a level of approval for using the land plot for each land use”: Lichana, paragraph 0090, “A feedback loop 110 is also used so that customer satisfaction may be incorporated into the dynamic optimization process. The data that is provided in the feedback loop may be raw data that is collected from actual residents [a level of approval ], and/or other entities, user input from the planner, or the data may be from the results of a model or simulation that is created. The feedback data may then be collected and stored in a database as described in the following figures and associated description. Thus, in one aspect, the Systems and Methods For Land-Use Development, Planning and Management is an optimization process for optimizing the allocation of services to improve quality of life in a land-use plan [the ranking of land uses associated with each land plot indicates a level of approval for using the land plot for each land use].”
Lichana and Suzuki are analogous arts as they are both related to resource allotment. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the application of resource allotment to land use of Lichana with the teachings of Suzuki to arrive at the present invention, in order to optimize allocation, as stated in Lichana, paragraph 0090, “Thus, in one aspect, the Systems and Methods For Land-Use Development, Planning and Management is an optimization process for optimizing the allocation of services to improve quality of life in a land-use plan.”
Claim 15 rejected under 35 U.S.C. 103 over Suzuki as modified by Yamaguchi in view of Kinney Jr. et al., US Patent No. 10,534,655 (hereafter Kinney).
Suzuki as modified by Yamaguchi teaches “[t]he method of claim 1.”
Suzuki further teaches (bold only) “comprising validating the allocation of the one or more resources based on the resource allocation data, the amounts of resources required by each category, and the rankings of the plurality of categories associated with each resource”: Suzuki, paragraph 0093, “Further, as shown in FIG. 12, the individual capability calculation unit 61 calculates individual capability data of each worker periodically (for example, every week) by using the individual capability history of each worker stored in the individual capability storage unit 62. For example, the individual capability calculation unit 61 extracts an individual capability history within a predetermined period (for example, three months) for each worker [the resource allocation data]”; Suzuki, paragraph 0101, “The required skilled workers number storage unit 64 stores the number of skilled workers required in each of the steps P1 to P5 as the required number of skilled workers for each step [the amounts of resources required by each category]”; Suzuki, paragraph 0097, “Further, the individual capability calculation unit 61 can also calculate step-specific comprehensive individual capability data and product-specific comprehensive individual capability data for each worker based on the individual capability data [the rankings of the plurality of categories associated with each resource]. That is, the individual capability calculation unit 61 can calculate an average of the rank XP1 of the individual capability of the first step P1 in the product X, the rank YP1 of the individual capability of the first step P1 in the product Y, and the rank ZP1 of the individual capability of the first step Pl in the product Z, and set a calculation result as step-specific comprehensive individual capability data OP1 of the first step P1. Further, similarly to the case of the step-specific comprehensive individual capability data OP1 of the first step P1, the individual capability calculation unit 61 can calculate step-specific comprehensive individual capability data OP2 to OPS of the second step P2, the third step P3, the fourth step P4, and the fifth step P5.”
Suzuki as modified by Yamaguchi does not explicitly teach (bold only) “comprising validating the allocation of the one or more resources based on the resource allocation data, the amounts of resources required by each category, and the rankings of the plurality of categories associated with each resource.”
Kinney teaches (bold only) “comprising validating the allocation of the one or more resources based on the resource allocation data, the amounts of resources required by each category, and the rankings of the plurality of categories associated with each resource”: Kinney, col. 2, lines 30–38, “Using the techniques described herein, a resource allocation score for jobs in a workload may be used to allocate usage of computing resources. A job scheduling system may determine a resource allocation score for a workload that has been supplied by a user. A resource allocation score may generally represent (at least in part) an estimated likelihood of successful execution of a set of jobs [validating the allocation of the one or more resources].”
Kinney and Suzuki are analogous arts as they are both related to resource allotment. It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the claimed invention to have combined the allotment validation of Kinney with the teachings of Suzuki to arrive at the present invention, in order to use an objective measure of allotment quality to generate better allotments, as stated in Kinney, col. 3, lines 6–8, “In this manner, the likelihood may be reduced of launching, on behalf of a user, a large number of concurrent jobs that fail.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sun et al., US Pre-Grant Publication No. 2020/0328984, discloses a method for resource allocation that matches resource limits to required quotas.
Haid et al., “Accommodating Employee Preferences in Algorithmic Worker-Workplace Allocation,” 2022, Human Factors in Management and Leadership, Vol. 55, 2022, 79–87, discloses a method for allocating employees to tasks that incorporates employee preferences.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VINCENT SPRAUL whose telephone number is (703) 756-1511. The examiner can normally be reached M-F 9:00 am - 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, MICHAEL HUNTLEY can be reached at (303) 297-4307. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/VAS/Examiner, Art Unit 2129
/MICHAEL J HUNTLEY/Supervisory Patent Examiner, Art Unit 2129
Prosecution Insights