A game-theory approach based on genetic algorithm for flexible job shop scheduling problem

In the paper, flexible job shop scheduling problem (FJSP) which joints the objective of maximizing the manufacturer's efficiency and the objective of maximizing the customer's delivery satisfaction is considered. An optimization model based on game theory is put forward for the FJSP. Therefore, the problem of FJSP is transferred into a game, in which all jobs and the manufacturer are regarded as players in the game. The players behave with the objective of maximizing their own profits. The manufacturer wants to minimize the makespan of all the jobs, whereas each job wants to minimize the own tardiness. Eventually they gain the equilibrium. In order to solve the game, Nash equilibrium (NE) searching approach based on genetic algorithm (GA) is designed and developed. The efficiency of the proposed approach is validated on several benchmark instances.