用混合量子算法求解模糊柔性作业车间调度问题  

Solving the Fuzzy Flexible Job Shop Scheduling Problem with Hybrid Quantun Algorithm

作　　者：刘晓冰[1] 焦璇[1] 黄明[2] 宁涛[2] 

机构地区：[1]大连理工大学管理学院,辽宁大连116023 [2]大连交通大学软件学院,辽宁大连116045

出　　处：《工业工程与管理》2015年第3期8-13,共6页Industrial Engineering and Management

基　　金：国家自然科学基金重点资助项目(61034003);国家科技支撑计划资助项目(2012BAF12B08);国家863计划资助项目(2012AA041402-4);辽宁省教育厅高校优秀人才青年学者成长计划资助项目(LJQ2013048);辽宁省教育厅科学研究资助项目(L2014183)

摘　　要：针对模糊环境下柔性作业车间的调度问题,以最小化最大完工时间、最小化成本和最小化惩罚值为目标,建立调度问题数学模型,提出了混沌量子粒子群算法。针对实际生产交货期模糊的特点,在量子粒子群算法基础上,提出引入混沌机制建立初始群的方法;针对量子个体的更新,提出了改进的量子旋转角计算方法;针对种群可能局部早熟收敛和后期多样性丢失的问题,利用混沌机制的遍历性,提出混沌局部优化策略;通过四个经典的调度算例验证了所提出算法能降低早熟概率和提高迭代搜索效率,与其他算法比较可以获得更多的非支配解。For the purpose of solving the flexible job-shop scheduling（FJSP）problem in the fuzzy environment,the simulation model is established aiming at minimizing completion time and costs,besides,a novel chaos quantum particle swarm optimization（CQPSO）algorithm is proposed.On the basis of the characteristics of the fuzzy production delivery time in actual production,the method of initializing population with chaos mechanism is introduced.To update the quantum individual,a novel method to improve the quantum rotating angle is proposed.To solve the problem of premature convergence and diversity loss for the population in the late,the chaos local optimization strategy using the ergodicity of chaos mechanism is proposed.The simulation results of four classical JSP instance demonstrate that the proposed algorithm can reduce the precocious probability and improve the efficiency of iterative search,comparing to other algorithms,more non-dominated solutions can be obtained.

关 键 词：多目标优化 模糊调度 柔性作业车间调度 量子粒子群算法 混沌机制 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]