Information processing device, information processing method, and program

Abstract

To further improve accuracy of acquiring a solution of a combination optimization problem.SOLUTION: An information processing device of the present disclosure includes: a selection unit which selects at least one solving device from among a plurality of solving devices set to solve a combination optimization problem with mutually different solving conditions; and an execution unit which executes the solving process with the selected solving device, and acquires an index for evaluating the performance of the solving device after the execution. The information processing device repeatedly implements a series of processes for selecting a solving device, executing the solving process with the selected solving device, and acquiring the index.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Simulated annealing is known as a method for solving combinatorial optimization problems, as described in Patent Document 1. In simulated annealing, when searching for a solution to an optimization problem, if a nearby solution has a good evaluation value, the algorithm will always transition to that nearby solution, but if a nearby solution has a bad evaluation value, the algorithm may transition probabilistically. The probability at this time is determined by the value of a set temperature parameter.

[0003] In this case, if the temperature parameter is high, the probability of transitioning to a solution with a poor evaluation value increases, allowing the system to escape from a local solution, but it may also move away from the optimal solution. Also, if the temperature parameter is low, the probability of transitioning to a solution with a poor evaluation value decreases, leading to convergence to a nearby local solution and making it impossible to escape from the local solution. For this reason, it is expected that the optimal solution can be reached by using simulated annealing to gradually lower the temperature over a sufficiently long period of time. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2019 / 234837 Summary of the Invention [Problem to be solved by the invention]

[0005] However, when solving combinatorial optimization problems in practice, simulated annealing must be performed in a finite time, and the accuracy of the final solution varies depending on the annealing conditions, such as the initial state of the solution and the temperature schedule. This creates a problem in that it is not possible to further improve the accuracy of solving combinatorial optimization problems.

[0006] Therefore, one of the objects of the present disclosure is to solve the above-mentioned problem that it is not possible to further improve the accuracy of solving combinatorial optimization problems. [Means for solving the problem]

[0007] An information processing device according to an embodiment of the present disclosure includes: a selection unit that selects at least one solution-finding device from among a plurality of solution-finding devices that are configured to solve combinatorial optimization problems under different solution-finding conditions; an execution unit that executes a solution-finding process by the selected solution-finding device and obtains an index for evaluating the performance of the solution-finding device after the execution; Equipped with selecting the solution-finding device, and executing a solution-finding process by the selected solution-finding device to repeatedly perform a series of processes for obtaining the index; The structure is as follows. Furthermore, an information processing method according to an embodiment of the present disclosure includes: selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as The structure is as follows. Furthermore, a program according to an embodiment of the present disclosure includes: selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as Execute the process, The structure is as follows. [Effects of the Invention]

[0008] With the above-described configuration, the present disclosure can further improve the accuracy of solving combinatorial optimization problems. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram illustrating an example of a configuration of an information processing device according to the present disclosure. [Figure 2] FIG. 1 is a diagram illustrating an example of a process performed by an information processing device according to the present disclosure. [Figure 3] FIG. 1 is a diagram illustrating an example of a process performed by an information processing device according to the present disclosure. [Figure 4] 10 is a flowchart illustrating an example of a processing operation of an information processing device according to the present disclosure. [Figure 5] FIG. 1 is a block diagram illustrating an example of a hardware configuration of an information processing device according to the present disclosure. [Figure 6] 1 is a block diagram illustrating an example of a configuration of an information processing device according to the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0010] First Embodiment A first embodiment of the present disclosure will be described with reference to the drawings, which may be relevant to any embodiment.

[0011] The information processing device in the present disclosure is used to prepare multiple annealers (hereinafter also referred to as "SA"), which are solution-finding devices that solve a predetermined combinatorial optimization problem, and select an annealer with a good evaluation that can obtain a good solution. The annealer searches for a solution to a combinatorial optimization problem by searching for a solution that minimizes energy using simulated annealing. When searching for a solution using simulated annealing, a transition is always made if the evaluation value of a neighboring solution is good. However, even if the evaluation value of a neighboring solution is poor, a transition occurs probabilistically, and the probability at this time is determined by a temperature parameter. Here, the term "solution-finding device" does not necessarily refer to a physical device, and may also refer to multiple annealing methods, etc. In other words, the term "solution-finding device" in the present disclosure refers to a method of searching for a solution to a combinatorial optimization problem.

[0012] The information processing device 10 is composed of one or more information processing devices each having a calculation device and a storage device. As shown in FIG. 1, the information processing device 10 includes a generation unit 11, a selection unit 12, and an execution unit 13. The functions of the generation unit 11, the selection unit 12, and the execution unit 13 can be realized by the calculation device executing a program for realizing each function stored in the storage device. The information processing device 10 also includes a question storage unit 15 and an SA information storage unit 16, which are realized by the storage device. Each configuration and operation will be described in detail below.

[0013] The problem storage unit 15 stores information representing the combinatorial optimization problem to be solved. An example of a combinatorial optimization problem is the traveling salesman problem. The traveling salesman problem is an optimization problem that, when the distances between cities are given, finds a route that minimizes the travel distance under the constraint that a salesman must visit every city once. However, the combinatorial optimization problem to be solved may be an optimization problem of any content.

[0014] Based on the information about the combinatorial optimization problem described above, the generation unit 11 generates an annealer (SA), which is a solution-finding device that solves the optimization problem (step S1 in FIG. 4). At this time, the generation unit 11 generates annealers with different solution-finding conditions. For example, the solution-finding conditions include an initial state (initial solution) and a temperature schedule that specifies temperature increases and decreases. Therefore, each generated annealer performs a different solution search operation and is in a different state after the solution-finding process is completed. In other words, after a predetermined time of simulated annealing, each annealer will have different values ​​representing performance, such as an evaluation value of the searched solution, the degree of constraint violation of the solution, and the degree of solution update. In this embodiment, the evaluation value of the solution after the annealer has completed a predetermined time of simulated annealing is treated as an index for evaluating the performance of the annealer. However, the index for evaluating the performance of the annealer is not limited to the evaluation value of the solution found, and the degree (frequency or rate) of constraint violation of the solution, the degree (frequency or rate) of update of the solution, or a value related to the execution of the solution-finding process by the annealer may also be used as an index for evaluating the performance of the annealer. Furthermore, a value calculated based on the evaluation value of the solution or a value based on a combination of the evaluation values ​​of the solution may also be used as an index.

[0015] Each annealer generated by the generation unit 11 is, for example, a model in which a combinatorial optimization problem with constraints is converted into a formulated model such as an Ising model or a QUBO (Quadratic Unconstrained Binary Optimization) model. As described above, different solution conditions are set for each annealer.

[0016] The generation unit 11 stores information on the multiple annealers with different solution-finding conditions that it has generated in the SA information storage unit 16. An SA pool as shown in Fig. 2 is set in the SA information storage unit 16, and information on each of the annealers that it has generated is stored in the SA pool. In Fig. 2, each graph represents each annealer itself, and for example, for each annealer, the solution-finding conditions set for the annealer as described above are stored as information on the annealer.

[0017] The SA information storage unit 16 stores information about each annealer itself, as well as SA information generated as the annealer performs a solution-finding process. FIG. 3 shows an example of SA information stored in the SA information storage unit 16. In this example, three annealers, SA1, SA2, and SA3, are stored in the SA pool, and identification information for each annealer is stored. As described below, the information processing device 10 repeatedly performs a series of processes, such as selecting an annealer and executing a solution-finding process. As shown in FIG. 3, the SA information stores identification information (#1, #2, . . .) for the "trial run" of the series of processes, as well as the "evaluation value" and "number of selections" of each annealer in the series of processes in each trial run. As described above, the "evaluation value" is the evaluation value (index) of the solution of each annealer after the series of processes has been performed. The "number of selections" is the cumulative number of times each annealer has been selected in the series of processes.

[0018] Furthermore, as shown in FIG. 3, the SA information storage unit 16 stores, as SA information, the behavior when selecting an annealer during a series of processing in each trial, represented as "search" or "utilization." Here, "search behavior" represents the behavior of randomly selecting an annealer from within the SA pool, and "utilization behavior" represents the behavior of selecting an annealer from within the SA pool based on the value of an index, which is the evaluation value of the annealer. Also stored as SA information is identification information for the annealer selected during a series of processing in each trial. Specific annealer selection behaviors will be described later.

[0019] Here, information on a plurality of annealers with different solution-finding conditions as described above may be stored in advance in the SA pool of the SA information storage unit 16. In other words, it is not always necessary for the generation unit 11 to generate a plurality of annealers, and information on a plurality of annealers generated by other devices or a plurality of annealers prepared in advance may be stored in the SA pool.

[0020] Next, the selection unit 12 and the execution unit 13 will be described. The selection unit 12 and the execution unit 13 repeatedly perform a series of processes, such as selecting an annealer from the SA pool and executing a solution-finding process using the selected annealer. An outline of the series of processes performed by the selection unit 12 and the execution unit 13 is shown in FIG. 2. As shown in this figure, the selection unit 12 and the execution unit 13 repeatedly perform a series of processes over multiple trials, such as selecting an annealer (SA) from the SA pool (symbol A1), performing a solution-finding process for the selected annealer for a predetermined time (symbol A2), determining an index, which is an evaluation value, from the state of the annealer after the solution-finding process is executed, updating and storing the index (symbol A3), and returning the selected annealer to the SA pool (symbol A4). The processes performed by the selection unit 12 and the execution unit 13 will be specifically described below.

[0021] The selection unit 12 selects at least one annealer from the SA pool in each trial of the series of processes described above (step S2 in FIG. 4). At this time, the selection unit 12 selects an annealer in accordance with each selection action set in each trial. As an example, the selection action is classified into an "exploratory action" and an "utilization action." The "exploratory action" randomly selects an annealer from the SA pool. The "utilization action" selects an annealer from the SA pool based on the value of an index, which is the evaluation value of the annealer. As an example, the "utilization action" selects the annealer with the best index, which is the evaluation value, in each trial.

[0022] In this embodiment, the selection unit 12 sets "exploratory behavior" with a preset probability p and sets "utilization behavior" with a probability (1-p) in each trial of the series of processes. As an example, when the probability p is set to 0.5, "exploratory behavior" is set and an annealer is randomly selected in the first trial, and "utilization behavior" is set in the second trial, and an annealer with the best index is selected. Note that the probability p may be any value, and may be a fixed value or a variable value. As an example of a case where the probability p is a variable value, the probability p is set to a larger value in the early stages of the trial, and many annealers are randomly selected based on "exploratory behavior." As the number of trials increases, the probability p is set to a smaller value, and many annealers with high index values ​​based on "utilization behavior" are selected.

[0023] When selecting an annealer for each trial, the selection unit 12 may select one annealer or multiple annealers. When the selection unit 12 selects multiple annealers, the "utilization behavior" may select a predetermined number of annealers in descending order of index.

[0024] In each trial of the series of processes, the execution unit 13 executes the solution-finding process using the annealer selected as described above for the corresponding trial (step S3 in FIG. 4). At this time, the execution unit 13 executes the solution-finding process using the selected annealer for a predetermined time that has been set in advance. Note that if multiple annealers are selected by the selection unit 12, the execution unit 13 may execute the solution-finding process using each annealer in sequence or in parallel.

[0025] The execution unit 13 then calculates an "evaluation value" of the solution, which is an index of the performance of the annealer after the solution-finding process has been executed, and updates and stores the value of this evaluation value as the SA information of the corresponding annealer in the SA information storage unit 16 (for example, the "evaluation value" column in FIG. 3). Note that the degree to which the evaluation value of the annealer can be improved after the solution-finding process is executed may be set in advance for each annealer, and the value of this degree of improvement is added to the previous evaluation value and updated each time a trial is executed. However, the evaluation value of the annealer may be calculated from the solution searched for by the annealer that was actually executed, or may be calculated based on any standard.

[0026] Furthermore, the execution unit 13 stores other SA information in the SA information storage unit 16 each time the solution-finding process is executed in each trial. For example, the execution unit 13 stores, as SA information, information on the set selected action, "search" or "utilize," identification information of the selected annealer (for example, the "selected SA" column in FIG. 3), and the cumulative "number of selections" of the annealer, in association with information identifying the corresponding trial (for example, "#1" in FIG. 3). However, part of the SA information may be stored in the selection unit 12 described above.

[0027] The selection unit 12 and the execution unit 13 then repeat the above-described series of processes over multiple trials. At this time, for example, the selection unit 12 and the execution unit 13 repeat the series of processes until a termination condition, such as the passage of a preset end time, is met (No in step S5 of FIG. 4). When the preset end time has passed and the termination condition is met (Yes in step S5 of FIG. 4), the selection unit 12 and the execution unit 13 stop repeating the series of processes. Then, the execution unit 13 outputs information about the annealer with the best "evaluation value" in the SA information storage unit 16 (step S6 of FIG. 4). For example, the execution unit 13 outputs SA information such as the identification information of the annealer and the value of the evaluation value at that time.

[0028] Here, referring to FIG. 3, an example of specific processing by the selection unit 12 and the execution unit 13 will be described. In this example, as described above, three annealers, namely SA1, SA2, and SA3, are stored in the SA pool, and a series of processes are executed in each trial from #1 to #7. In this example, the selection unit 12 sets "exploratory behavior" with a probability p=0.5 for each trial, sets "utilization behavior" with a probability (1-p), and selects one annealer. Furthermore, in this example, the degree of improvement in the evaluation value of each annealer due to the execution of the solution-finding process in one trial is set in advance. For example, the evaluation value of the annealer "SA1" is increased by "+100", the evaluation value of the annealer "SA2" by "+10", and the evaluation value of the annealer "SA3" by "+50".

[0029] First, in the first trial (#1), the selection behavior is set to "search behavior," and the selection unit 12 randomly selects an annealer from the SA pool. At this time, it is assumed that the annealer "SA2" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA2," and updates the SA information, such as the evaluation value. As a result, in the SA information column for the next trial, the second trial (#2), the "evaluation value" of the annealer "SA2" is updated to "10," and the "number of selections" is updated to "1."

[0030] Subsequently, in the second trial (#2), the selection action is set to "utilization action," and the selection unit 12 selects the annealer with the highest evaluation value from the SA pool. Then, the annealer "SA2" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA2," and updates the SA information, such as the evaluation value. As a result, in the SA information column for the next trial, the third trial (#3), the "evaluation value" of the annealer "SA2" is updated to "20," and the "number of selections" is updated to "2."

[0031] Subsequently, in the third trial (#3), the selection behavior is set to "search behavior," and the selection unit 12 randomly selects an annealer from the SA pool. At this time, it is assumed that the annealer "SA1" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA1," and updates the SA information such as the evaluation value. As a result, in the SA information column for the next trial, the fourth trial (#4), the "evaluation value" of the annealer "SA1" is updated to "100," and the "number of selections" is updated to "1."

[0032] Next, in the fourth trial (#4), the selection action is set to "utilization action," and the selection unit 12 selects the annealer with the highest evaluation value from the SA pool. Then, the annealer "SA1" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA1," and updates the SA information, such as the evaluation value. As a result, in the SA information column for the next trial, the fifth trial (#5), the "evaluation value" of the annealer "SA1" is updated to "200," and the "number of selections" is updated to "2."

[0033] Next, in the fifth trial (#5), the selection action is set to "utilization action," and the selection unit 12 selects the annealer with the highest evaluation value from the SA pool. Then, the annealer "SA1" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA1," and updates the SA information, such as the evaluation value. As a result, in the SA information column for the next trial, the sixth trial (#6), the "evaluation value" of the annealer "SA1" is updated to "300," and the "number of selections" is updated to "3."

[0034] Subsequently, in the sixth trial (#6), the selection behavior is set to "search behavior," and the selection unit 12 randomly selects an annealer from the SA pool. At this time, it is assumed that the annealer "SA3" is selected. Then, the execution unit 13 executes a solution-finding process using the selected annealer "SA3," and updates the SA information, such as the evaluation value. As a result, in the SA information column for the next trial, the seventh trial (#7), the "evaluation value" of the annealer "SA3" is updated to "50," and the "number of selections" is updated to "1."

[0035] Then, when a termination condition, such as the passage of a preset termination time, is met, the execution unit 13 checks the SA information in the SA information storage unit 16 and outputs information on the annealer with the best "evaluation value." For example, in the SA information for the seventh trial (#7) shown in Fig. 3, the evaluation value of the annealer "SA1" is the best, so information such as identification information that identifies the annealer "SA1" is output.

[0036] This makes it possible to obtain information on the annealer "SA1" with the best evaluation value when solving combinatorial optimization problems. This makes it possible to prioritize resource allocation to such annealers and use them in the solution process. As a result, it is possible to further improve the accuracy of solving combinatorial optimization problems.

[0037] 3, the action selected by the selection unit 12 is alternately switched between "search action" and "utilization action" each time a series of processes is performed once or multiple times. As a result, each annealer is selected and a solution-finding process is executed, making it possible to evaluate all annealers.

[0038] When the selection unit 12 randomly selects an annealer in the "search behavior", the annealer may be selected completely randomly, or the annealer may be selected by another method. For example, the selection unit 12 may select an annealer in the "search behavior" by using a selection probability s i In this case, the annealer may be selected according to the selection probability s i can be calculated, for example, by the following formula 1.

number

[0039] As a result, each annealer is randomly selected and the solution-finding process is executed while taking into account the index of the annealer, and all annealers can be evaluated.

[0040] Furthermore, the selection unit 12 may select an annealer based on the number of times each annealer has been selected in the "search behavior." For example, the selection unit 12 may select each annealer at least once in the "search behavior" and repeatedly perform a series of processes. As an example, in each trial, the selection unit 12 may first prioritize selecting all annealers in order once each and repeatedly perform a series of processes, and then repeatedly perform the series of processes thereafter. In this case, after selecting all annealers once each and repeatedly performing a series of processes, one or more annealers may be selected in descending order of the score expressed by the following formula 2.

number

[0041] As a result, an annealer that has been selected less frequently is actively selected to execute the solution-finding process, and all annealers can be evaluated. Note that the selection unit 12 may select an annealer based on the score of Equation 2 alone, or may select an annealer according to a criterion based on the number of selections.

[0042] The above-mentioned generation unit 11 may generate a new annealer and add it to the SA pool for storage while the selection unit 12 and execution unit 13 are repeatedly performing a series of processes. This allows the newly added annealer to be selected and the solution-finding process to be executed, making it possible to evaluate all annealers.

[0043] <Second embodiment> Next, a second embodiment of the present disclosure will be described with reference to the drawings. In this embodiment, an outline of the information processing device and the like described in the above-mentioned embodiment is shown. Note that the drawings may be relevant to any of the embodiments.

[0044] First, a description will be given of the hardware configuration of the information processing device 100 in the present disclosure. The information processing device 100 is configured as a general information processing device, and is equipped with the following hardware configuration, as an example, as shown in FIG. ·CPU(Central Processing Unit)101(Arithmetic unit) ROM (Read Only Memory) 102 (storage device) RAM (Random Access Memory) 103 (storage device) Programs 104 loaded into RAM 103 A storage device 105 for storing a group of programs 104 A drive device 106 that reads and writes from a storage medium 110 external to the information processing device A communication interface 107 that connects to a communication network 111 outside the information processing device Input / output interface 108 for inputting and outputting data Bus 109 connecting each component

[0045] 5 shows an example of the hardware configuration of the information processing device 100, and the hardware configuration of the information processing device is not limited to the above-described case. For example, the information processing device may be configured with a part of the above-described configuration, such as excluding the drive device 106. Furthermore, the information processing device may use a GPU (Graphics Processing Unit), a DSP (Digital Signal Processor), an MPU (Micro Processing Unit), an FPU (Floating point number Processing Unit), a PPU (Physics Processing Unit), a TPU (Tensor Processing Unit), a quantum processor, a microcontroller, or a combination thereof, instead of the above-described CPU.

[0046] The information processing device 100 can be equipped with the selection unit 121 and execution unit 122 shown in Fig. 6 by having the CPU 101 acquire and execute the program group 104. The program group 104 is stored in advance in the storage device 105 or the ROM 102, for example, and is loaded into the RAM 103 and executed by the CPU 101 as needed. The program group 104 may be supplied to the CPU 101 via the communication network 111, or may be stored in advance in the storage medium 110, and the drive device 106 may read out the programs and supply them to the CPU 101. However, the selection unit 121 and execution unit 122 described above may be constructed using dedicated electronic circuits for realizing such means.

[0047] The selection unit 121 selects at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions. The execution unit 122 executes a solution-finding process by the selected solution-finding device and obtains an index for evaluating the performance of the solution-finding device after execution. Then, a series of processes is repeated, including selecting the solution-finding device, executing a solution-finding process by the selected solution-finding device, and obtaining the index.

[0048] With the above-described configuration, the present disclosure can evaluate any annealing device and further improve the accuracy of solving combinatorial optimization problems.

[0049] At least one of the functions of the selection unit 121 and the execution unit 122 described above may be executed by an information processing device installed and connected anywhere on the network, that is, may be executed by so-called cloud computing.

[0050] The above-described program can be stored and supplied to a computer using various types of non-transitory computer-readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (e.g., flexible disks, magnetic tapes, hard disk drives), magneto-optical recording media (e.g., magneto-optical disks), CD-ROMs (Read Only Memory), CD-Rs, CD-R / Ws, and semiconductor memories (e.g., mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (Random Access Memory)). The program can also be supplied to a computer by various types of transitory computer-readable media. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. The transitory computer-readable media can supply the program to a computer via a wired communication path such as an electric wire or optical fiber, or via a wireless communication path.

[0051] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each of the above-described embodiments can be combined with other embodiments as appropriate.

[0052] <Additional Notes> Some or all of the above embodiments may be described as follows: The following provides an overview of the configurations of an information processing device, an information processing method, and a program according to the present disclosure. However, the present disclosure is not limited to the configurations described in the following supplementary notes. Note that the configurations described in Supplements 2 to 8.3 below, which are dependent on Supplementary Note 1, and some or all of the functions of the configurations, may also be dependent on other Supplements 9 and 10 in the same dependent relationship as Supplements 2 to 8.3. Furthermore, not limited to Supplements 1, 9, and 10, but also within the scope of the above-described embodiments, similar hardware, software, various recording means for recording software, or systems may be similarly made to be dependent on the configurations described as Supplements and some or all of the functions of the configurations. (Appendix 1) a selection unit that selects at least one solution-finding device from among a plurality of solution-finding devices that are configured to solve combinatorial optimization problems under different solution-finding conditions; an execution unit that executes a solution-finding process by the selected solution-finding device and obtains an index for evaluating the performance of the solution-finding device after the execution; Equipped with selecting the solution-finding device, and executing a solution-finding process by the selected solution-finding device to repeatedly perform a series of processes for obtaining the index; Information processing device. (Appendix 2) 10. The information processing device according to claim 1, When the series of processes is repeatedly performed, the execution unit updates and stores the index of the solution-finding device obtained by performing the solution-finding process; after repeating the series of processes so as to satisfy a preset condition, the execution unit outputs information about the solution-finding device based on the index; Information processing device. (Appendix 2.1) 10. The information processing device according to claim 2, after repeating the series of processes so as to satisfy a preset condition, the execution unit outputs information of the solution finding device corresponding to the index that is best according to a preset criterion. Information processing device. (Appendix 3) 10. The information processing device according to claim 1, the selection unit randomly selecting the solution solving device when repeating the series of processes. Information processing device. (Appendix 4) 4. The information processing device according to claim 3, and when the series of processes is repeatedly performed, the selection unit selects the solution finding device with a probability based on a value of the index. Information processing device. (Appendix 5) 10. The information processing device according to claim 1, When the series of processes is repeatedly performed, the selection unit randomly selects the solution solving device, and selects the solution solving device based on the value of the index. Information processing device. (Appendix 6) 6. The information processing device according to claim 5, When the series of processes is repeated, the selection unit switches between randomly selecting the solution-finding device and selecting the solution-finding device based on the value of the index each time the series of processes is performed once or multiple times. Information processing device. (Appendix 7) 10. The information processing device according to claim 1, When the series of processes is repeated, the selection unit selects the solution-finding device based on the number of times the solution-finding device has been selected. Information processing device. (Appendix 8) 8. The information processing device according to claim 7, When the series of processes is repeatedly performed, the selection unit selects all of the solution finding devices at least once. Information processing device. (Appendix 8.1) 10. The information processing device according to claim 1, When the series of processes is repeatedly performed, the execution unit obtains, as the index, a value based on an evaluation value of a solution obtained by the solution-finding device that executed the solution-finding process. Information processing device. (Appendix 8.2) 10. The information processing device according to claim 1, When the series of processes is repeatedly performed, the execution unit obtains, as the index, a value based on the degree of constraint violation of the solution obtained by the solution-finding device that executed the solution-finding process. Information processing device. (Appendix 8.3) 10. The information processing device according to claim 1, When the series of processes is repeatedly performed, the execution unit obtains, as the index, a value based on a degree of update of the solution by the solution-finding device that executed the solution-finding process. Information processing device. (Appendix 9) selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as Information processing methods. (Appendix 9.1) 10. The information processing method according to claim 9, When repeating the series of processes, the index of the solution-finding device obtained by executing the solution-finding process is updated and stored; and outputting information about the solution-finding device based on the index after repeating the series of processes so as to satisfy a preset condition. Information processing methods. (Appendix 9.2) 10. The information processing method according to claim 9, randomly selecting the solver when repeating the series of processes; Information processing methods. (Appendix 9.3) 10. The information processing method according to claim 9, selecting the solution solving device randomly when repeating the series of processes; and selecting the solution solving device based on the value of the index. Information processing methods. (Appendix 9.4) 9.3. An information processing method according to claim 9.3, comprising: When the series of processes is repeated, switching between randomly selecting the solution-finding device and selecting the solution-finding device based on the value of the index each time the series of processes is performed once or multiple times. Information processing methods. (Appendix 9.5) 10. The information processing method according to claim 9, When repeating the series of processes, the solution-finding device is selected based on the number of times the solution-finding device has been selected. Information processing methods. (Appendix 9.6) 9.5. An information processing method according to claim 9.5, comprising: selecting all of the solvers at least once when repeating the series of processes; Information processing methods. (Appendix 10) selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as A program for executing a process. [Explanation of symbols]

[0053] 10. Information processing equipment 11 Generation part 12 Selection section 13 Executive Department 15 Problem storage 16 SA information storage unit 100 Information processing device 101 CPU 102 ROM 103 RAM 104 Programs 105 Storage device 106 Drive device 107 Communication Interface 108 Input / Output Interface 109 Bus 110 Storage medium 111 Communication Network 121 Selection Section 122 Executive Department

Claims

1. a selection unit that selects at least one solution-finding device from among a plurality of solution-finding devices that are configured to solve combinatorial optimization problems under different solution-finding conditions; an execution unit that executes a solution-finding process by the selected solution-finding device and obtains an index for evaluating the performance of the solution-finding device after the execution; Equipped with selecting the solution-finding device, and executing a solution-finding process by the selected solution-finding device to repeatedly perform a series of processes for obtaining the index; Information processing device.

2. 2. The information processing device according to claim 1, When the series of processes is repeatedly performed, the execution unit updates and stores the index of the solution-finding device obtained by performing the solution-finding process; after repeating the series of processes so as to satisfy a preset condition, the execution unit outputs information about the solution-finding device based on the index; Information processing device.

3. 2. The information processing device according to claim 1, the selection unit randomly selecting the solution solving device when repeating the series of processes. Information processing device.

4. 4. The information processing device according to claim 3, and when the series of processes is repeatedly performed, the selection unit selects the solution finding device with a probability based on a value of the index. Information processing device.

5. 2. The information processing device according to claim 1, When the series of processes is repeatedly performed, the selection unit randomly selects the solution solving device, and selects the solution solving device based on the value of the index. Information processing device.

6. 6. The information processing device according to claim 5, When the series of processes is repeated, the selection unit switches between randomly selecting the solution-finding device and selecting the solution-finding device based on the value of the index each time the series of processes is performed once or multiple times. Information processing device.

7. 2. The information processing device according to claim 1, When the series of processes is repeated, the selection unit selects the solution-finding device based on the number of times the solution-finding device has been selected. Information processing device.

8. 8. The information processing device according to claim 7, When the series of processes is repeatedly performed, the selection unit selects all of the solution finding devices at least once. Information processing device.

9. selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as Information processing methods.

10. selecting at least one solution-finding device from among a plurality of solution-finding devices configured to solve combinatorial optimization problems under different solution-finding conditions; Execute a solution-finding process using the selected solution-finding device, and obtain an index for evaluating the performance of the solution-finding device after the execution. Repeat a series of processes such as A program for executing a process.

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