基于博弈粒子群算法的混流混合车间调度研究

Game theory and particle swarm optimization for mixed-model hybrid-shop scheduling problem

为了有效解决混流混合车间生产调度的全局优化问题,同时考虑部件车间、总装车间的齐套及平顺化要求,部件车间与零件车间缓存区存量控制要求,建立了以总装车间部件平顺化、部件车间齐套性和加工车间缓存区库存最小为优化指标的多目标调度模型.同时为解决多目标调度目标之间的矛盾关系,运用博弈粒子群算法进行求解.算法通过PSO对各车间按不同优化指标进行搜索求解并加入博弈理论以解决陷入单目标局部最优的缺陷,从而获得总生产系统全局最优.最后运用实例对模型和算法进行有效性验证.

The paper focused on solving the scheduling global optimization problem for mixed- model hybrid-shop, which consider the request of complete kit part consumption and the inventory control of buffer zone between job shop and Flow shop, then three objectives are given： minimizing the total variation in parts consumption in the assembly line, complete kitting of parts in the part line and minimizing buffer in the job shop. Then the GPSO algorithm is used to solve the problem of contradiction among the multi-objective scheduling objectives. The algorithm can use PSO to search local optimum of each part then the game-theory try to solve the problem to get the global optimum. Finally, an example was given to test the model and algorithm, and the results prove the method is effective and excellent.