Game Theoretical Approach for Customer Driven Job Scheduling Considering Carbon Emissions In Service-Oriented Manufacturing

This paper presents a novel scheduling solution for optimizing the carbon emissions and makespan of each job from different customers in service-oriented manufacturing environments. The paper first presents a new job scheduling problem considering carbon emissions by distinguishing the concepts and requirements of job scheduling in the service-oriented manufacturing environment from those in the traditional manufacturing environment. Secondly, a game-theory mathematical model is constructed to deal with this new job scheduling problem. In this model, the scheduling problem is formulated as an N-person non-cooperative game with complete information, where the players refer to the jobs submitted by different customers, a set of strategies of each player refer to machines in a service-oriented manufacturing workshop, and the payoffs refer to the makespan and carbon emissions of each job. Therefore, obtaining the optimal scheduling results is determined by the Nash Equilibrium (NE) point of this game. To find the NE point, a genetic algorithm combining local search is developed to effectively solve the above model. Finally, simulation case is designed and the results demonstrate the feasibility of the approach.