OPTIMIZATION METHOD, OPTIMIZATION APPARATUS AND PROGRAM

1 . An optimization method executed by a computer including a memory and a processor, the optimization method comprising:

receiving as input an acceptance probability function indicating a probability that each participant participating in a crowdsourcing market accepts a price, and a matching value indicating a value when each resource in the crowdsourcing market is allocated to each participant;

formulating a first optimization problem for determining an optimal price that maximizes a profit of a provider of the crowdsourcing market using the acceptance probability function and the matching value; and

calculating the optimal price by solving the first optimization problem according to a feature of the acceptance probability function.

2 . The optimization method according to claim 1 , wherein in the optimization procedure, the optimal price is calculated by transforming the first optimization problem into a second optimization problem using an approximate value of an objective function of the first optimization problem and solving the second optimization problem.

3 . The optimization method according to claim 2 , wherein an optimal solution of the second optimization problem is a solution in which a degree of approximation of 3 is guaranteed for an optimal solution of the first optimization problem.

4 . The optimization method according to claim 2 , wherein denoting an index representing each of the participants as i, a variable representing the price as x, and an acceptance probability function of the participant i as Si(x),

in the optimization procedure, when the acceptance probability function Si(x) is represented by a linear function with upper and lower limits, the optimal price is calculated by transforming the second optimization problem into a minimum convex secondary cost flow problem and solving the minimum convex secondary cost flow problem, and

when the acceptance probability function Si(x) is bijective and each function represented by 1−Si(x) is a Monotone hazard rate function, the optimal price is calculated by transforming the second optimization problem into a minimum convex cost flow problem and solving the minimum convex cost flow problem.

5 . The optimization method according to claim 4 , wherein in the optimization procedure, when the acceptance probability function Si(x) is not represented by a linear function with upper and lower limits and the acceptance probability function Si(x) is not bijective or each function represented by 1−Si(x) is not a Monotone hazard rate function, the optimal price is calculated by solving the second optimization problem using a heuristic solution including Bayesian optimization and simulated annealing.

6 . An optimization apparatus comprising:

a memory; and

a processor configured to

receive as input an acceptance probability function indicating a probability that each participant participating in a crowdsourcing market will accept a price, and a matching value indicating a value when each resource in the crowdsourcing market is allocated to each participant;

formulate a first optimization problem for determining an optimal price that maximizes a profit of a provider of the crowdsourcing market using the acceptance probability function and the matching value; and

calculate the optimal price by solving the first optimization problem according to a feature of the acceptance probability function.

7 . A non-transitory computer-readable recording medium having computer-readable instructions stored thereon, which when executed, cause a computer to execute the optimization method according to claim 1 .