Game theory-based Cooperation of Process Planning and Scheduling

One of the significant trends in manufacturing planning is to make computer automated process planning and scheduling to work more cooperatively. To build up cooperative process planning and scheduling (CPPS), in this research, three game theory- based strategies, i.e., Pareto strategy, Nash strategy and Stackelberg strategy, have been introduced to analyze the cooperation of the two functions in a systematic way. Modern heuristic algorithms, including particle swarm optimization (PSO), simulated annealing (SA) and genetic algorithm (GA), have been developed and applied to the CPPS problem to identify targeted solutions efficiently from the vast search space caused by the complexity of the problem. Meanwhile, adaptive strategies have been developed to accommodate dynamic changes in job shops.