Abstract: From the perspective of viewing customer’s competition requirements and on the basis of analyzing the goal of each manufacturing task submitted by correspondent customer maximizing its own payoffs (mainly focusing on the finishing time of each manufacturing task), together with the deficiency of traditional strategies, methods and models of task schedule, a non-cooperation game model with complete information for task schedule is presented and established. In this task schedul-ing model, the players correspond to the jobs submitted respec-tively by related customers, the strategies of each job corre-spond to the selectable geographical distributive machines re-lated to the processes of this job, and the payoff of each job is defined as the reciprocal of its finishing time. As such, obtain-ing the optimal scheduling results is determined by the Nash equilibrium (NE) point of this game. In order to find the NE point, genetic algorithm is introduced. A numerical case study is given to demonstrate the feasibility of above methods.

Key words: Nash equilibrium point, Non-cooperative game, Genetic algorithm, Task schedule