模糊环境下的差异作业单机批调度优化问题的研究

Research on optimal scheduling single batch-processing machine with non-identical job sizes under fuzzy enviroment

针对现实生产制造系统中存在的时间参数模糊化问题,用梯形模糊数表征时间参数,给出了一种具有模糊加工时间和模糊批次间隔的、以最小化制造跨度为目标的模糊差异作业单机批调度问题模型。在对模糊差异作业单机批调度问题进行有效求解方面,针对基本粒子群算法容易陷入局部最优的问题,给出了一种基于遗传操作的混合粒子群算法。利用遗传算法思想对粒子进行交叉、变异操作,增强了算法跳出局部最优的能力。仿真实验验证了该算法具有可行性和有效性。

To solve the problems correlated with fuzzy temporal parameter in real manufacture system,based on trapezoidal fuzzy number,this paper introduced a fuzzy single batch-processing machine with non-identical job sizes（NSBM） model aiming at minimized makespan which had fuzzy processing time of the batches and fuzzy intervals among the batches firstly.After that,aiming at the problems of easily getting into the local optimum of basic particle swarm optimization（PSO） algorithm,proposed a hybrid PSO algorithm based on crossover and mutation operations of genetic algorithm for the fuzzy NSBM problem above,which helped the algorithm to break away from the local optimum.At last,through the analysis of the simulating experiment results,the feasibility and efficency of the algorithm are approved.