【摘要】 为了解决多资源约束下的作业车间调度问题,提出了一种改进智能水滴算法.该算法采用了基于工序与加工机器相融合的两层编码方式建立问题和算法的映射关系,运用随机方法初始化产生可行解,结合精英保留策略加快算法的收敛速度,嵌入迭代局部搜索算法以增强算法的全局搜索能力,并来解决影响车间调度的3个主要成本因素,即最小化延期成本、最小化人工成本和最小化设备运行成本.通过实例的收敛性能对比,证明算法具有优秀的全局开发能力和收敛性.实验表明了该算法能够有效求解双资源约束车间调度问题.更多还原

【Abstract】 In order to solve the problem of job shop scheduling with multi resource constraints,an improved water drop algorithm is established.It adopts encoding method of the integration process and processing machine.Also it uses random method to initialize the generation of feasible solutions.Besides,it combines with the elite strategy and iterated local search algorithm.This algorithm is aimed to solve the three main factors:minimizing the delay cost,minimizing the labor cost and minimizing the equipment cost.At last,after comparing the convergence performance,the good global development capability and convergence have been approved.The model and the algorithm are proved to be effective in solving job shop scheduling problem.更多还原