Provided is an apparatus including a processor and one or more computer readable mediums collectively including instructions that, when executed by the processor, cause the processor to: acquire a candidate for a solution of an optimization problem for optimizing a third objective function based on a first objective function and a second objective function; obtain, as another candidate for the solution of the optimization problem, a solution that optimizes the second objective function under a constraint corresponding to a value of the first objective function for the acquired candidate; and select the solution of the optimization problem from among the plurality of candidates for the solution of the optimization problem. Also provided as the first aspect are a method and non-transitory computer readable storage medium.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. An apparatus comprising: a processor; and one or more computer readable mediums collectively including instructions that, when executed by the processor, cause the processor to: acquire a candidate for a solution of an optimization problem for optimizing a third objective function based on a first objective function and a second objective function; obtain, as another candidate for the solution of the optimization problem, a solution that optimizes the second objective function under a constraint corresponding to a value of the first objective function for the acquired candidate; and select the solution of the optimization problem from among the plurality of candidates for the solution of the optimization problem. 2. The apparatus according to claim 1, wherein the second objective function has an objective function value based on a sum of objective function values for partial problems of the optimization problem. 3. The apparatus according to claim 2, wherein the first objective function has an objective function value based on a largest value or a smallest value of the objective function values for the plurality of partial problems obtained by dividing the optimization problem. 4. The apparatus according to claim 3, wherein the obtaining the other candidate for the solution of the optimization problem includes obtaining an optimal solution that satisfies the constraint for each of the plurality of partial problems obtained by dividing the optimization problem. 5. The apparatus according to claim 4, wherein: the instructions further cause the processor to store in a storage section, in association with at least one partial problem among the plurality of partial problems, an objective function value of the at least one partial problem corresponding to the first objective function and an objective function value of the at least one partial problem corresponding to the second objective function; and the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes, for the at least one partial problem, using an objective function value stored in relation to the second objective function, if an objective function value stored in relation to the first objective function satisfies the constraint. 6. The apparatus according to claim 5, wherein the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes, for the at least one partial problem, obtaining a solution that optimizes an objective function value relating to the second objective function in the at least one partial problem under the constraint, if an objective function value stored in relation to the first objective function does not satisfy the constraint. 7. The apparatus according to claim 5, wherein the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes updating content of the storage section by using the obtained objective function value relating to the second objective function in the at least one partial problem under the constraint. 8. The apparatus according to claim 1, wherein a value of the third objective function is defined as the sum of the value of the first objective function and the value of the second objective function. 9. The apparatus according to claim 1, wherein the constraint corresponding to the value of the first objective function is an upper bound of the first objective function. 10. The apparatus according to claim 1, wherein: the selecting the solution of the optimization problem includes updating the selected candidates for the solution of the optimization problem; and the acquiring the candidate for the solution of the optimization problem includes repeating the obtaining the other candidate for the solution of the optimization problem and the selecting the solution of the optimization problem until there are no more solutions that optimize the second objective function. 11. The apparatus according to claim 1, wherein the selecting the solution of the optimization problem includes selecting the candidate having a lower value from among the plurality of candidates for the solution of the optimization problem. 12. A method comprising: acquiring a candidate for a solution of an optimization problem for optimizing a third objective function based on a first objective function and a second objective function; obtaining, as another candidate for the solution of the optimization problem, a solution that optimizes the second objective function under a constraint corresponding to a value of the first objective function for the acquired candidate; and selecting the solution of the optimization problem from among the plurality of candidates for the solution of the optimization problem. 13. The method according to claim 12, wherein the second objective function has an objective function value based on a sum of objective function values for partial problems of the optimization problem. 14. The method according to claim 13, wherein the first objective function has an objective function value based on a largest value or a smallest value of the objective function values for the plurality of partial problems obtained by dividing the optimization problem. 15. The method according to claim 14, wherein the obtaining the other candidate for the solution of the optimization problem includes obtaining an optimal solution that satisfies the constraint for each of the plurality of partial problems obtained by dividing the optimization problem. 16. The method according to claim 15, further comprising: storing in a storage section, in association with at least one partial problem among the plurality of partial problems, an objective function value of the at least one partial problem corresponding to the first objective function and an objective function value of the at least one partial problem corresponding to the second objective function, and wherein the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes, for the at least one partial problem, using an objective function value stored in relation to the second objective function, if an objective function value stored in relation to the first objective function satisfies the constraint. 17. The method according to claim 16, wherein the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes, for the at least one partial problem, obtaining a solution that optimizes an objective function value relating to the second objective function in the at least one partial problem under the constraint, if an objective function value stored in relation to the first objective function does not satisfy the constraint. 18. The method according to claim 16, wherein the obtaining the optimal solution that satisfies the constraint for each of the plurality of partial problems includes updating content of the storage section by using the obtained objective function value relating to the second objective function in the at least one partial problem under the constraint. 19. The method according to claim 12, wherein: the selecting the solution of the optimization problem includes updating the selected candidates for the solution of the optimization problem; and the acquiring the candidate for the solution of the optimization problem includes repeating the obtaining the other candidate for the solution of the optimization problem and the selecting the solution of the optimization problem until there are no more solutions that optimize the second objective function. 20. A computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to: acquire a candidate for a solution of an optimization problem for optimizing a third objective function based on a first objective function and a second objective function; obtain, as another candidate for the solution of the optimization problem, a solution that optimizes the second objective function under a constraint corresponding to a value of the first objective function for the acquired candidate; and select the solution of the optimization problem from among the plurality of candidates for the solution of the optimization problem.