基于改进灰熵并行优化量子状态转移算法求解MOJSP问题  

Quantum state transfer algorithm based on improved grey entropy parallel optimization for solving MOJSP

作　　者：吴贝贝 李喆 WU Beibei;LI Zhe(College of Electrical Engineering,Xinjiang University,Urumqi 830047,China;Center of Network and Information Technology,Xinjiang University,Urumqi 830046,China)

机构地区：[1]新疆大学电气工程学院,新疆乌鲁木齐830047 [2]新疆大学网络与信息技术中心,新疆乌鲁木齐830046

出　　处：《现代电子技术》2020年第10期69-75,共7页Modern Electronics Technique

基　　金：国家自然科学基金:复杂产品分布式快速协同仿真优化方法研究及其应用(51575469);国家自然科学基金:集群风电系统混沌动力学行为分析与控制研究(51767022)。

摘　　要：为了解决多目标作业车间调度问题(MOJSP),提出一种改进灰熵并行关联度的量子状态转移算法(QSTA)。构建以最大完工时间、最大拖期时间及总流程时间皆最短的多目标作业车间调度问题模型,利用灰熵权值计算适应度值来引导算法的进化,并将该方法应用于含容忍策略的QSTA中解决MOJSP问题。仿真结果表明,改进灰熵并行关联度引导QSTA求解MOJSP问题的可行性和有效性,其解优于其他三种智能优化算法,是解决作业车间生产调度问题的一种高效方法。A quantum state transition algorithm(QSTA)with improved gray entropy parallel correlation degree is proposed to solve the MOJSP(multi-objective job-shop scheduling problem). A MOJSP model is established with the maximum completion time,the maximum delay time and the total process time are the shortest,and the gray entropy weight is used to calculate the fitness value to guide the evolution of the algorithm. This method is applied into the QSTA with tolerance policy to solve the MOJSP. The simulation results show that the improved grey entropy parallel correlation degree guides QSTA is feasible and effective in solving the MOJSP,and its solution is better than that of other three intelligent optimization algorithms,which is an efficient method to solve the MOJSP.

关 键 词：MOJSP 量子状态转移 MOJSP建模 灰色关联分析 容忍机制 仿真分析 

分 类 号：TN911.2-34[电子电信—通信与信息系统] TP301.06[电子电信—信息与通信工程]