基于总加权完成时间的可重入混合流水车间调度问题  

Reentrant hybrid flowshop scheduling problem based on total weighted completion time

作　　者：轩华[1] 李冰[1] 罗书敏 王薛苑[1] XUAN Hua;LI Bing;LUO Shu-min;WANG Xue-yuan(School of Management Engineering,Zhengzhou University,Zhengzhou 450001,China)

机构地区：[1]郑州大学管理工程学院,郑州450001

出　　处：《控制与决策》2018年第12期2218-2226,共9页Control and Decision

基　　金：教育部人文社会科学研究基金项目(15YJC630148);国家自然科学基金项目(U1604150);郑州大学优秀青年教师发展基金项目(1421326092)

摘　　要：研究以最小化总加权完成时间为目标的可重入混合流水车间调度问题(RHFS-TWC),并构建问题的整数规划模型.根据模型的特点,设计基于二维矩阵组的调度解编码方案,结合NEH启发式算法确定工件初始加工顺序,生成高质量初始调度解群.为避免算法陷入早熟及扩大解的搜索空间,给出IGA的遗传参数自适应调整策略,最终形成NEH-IGA融合求解策略.针对不同规模问题分别用传统GA、基于遗传参数自适应调整的IGA、NEH启发式、NEH-IGA算法进行仿真测试,仿真结果表明NEH启发式和遗传参数自适应动态调整策略的引入有效改善了原有GA的求解能力, NEH-IGA算法在求解RHFS-TWC问题方面优势明显.This paper discusses a reentrant hybrid flowshop scheduling problem with the objective of minimizing total weighted completion time.An integer programming model is then developed.The scheduling coding scheme of two- dimensional matrix is designed based on the features of the model.Then,the initial job processing sequence is obtained using NEH heuristic in order to generate the initial scheduling population with high quality.The self-adaptive adjustment strategy of the genetic parameters in improved genetic algorithm(IGA)is proposed to avoid the early maturing of the algorithm and expands the search space.Thus the NEH-IGA algorithm is provided combined with the above improvement. Simulation experiments are perfomed on different sized problems respectively using the traditional GA,IGA based on the self-adaptive adjustment of genetic parameters,NEH heuristic and NEH-IGA.Numerical results show that the introdution of NEH heuristic and the self-adaptive adjustment strategy of genetic parameters can improve the solution ability of the original GA effectively.The NEH-IGA has more advantage in terms of solving the RHFS-TWC problem.

关 键 词：总加权完成时间 可重入混合流水车间调度 运输时间 NEH-IGA算法 

分 类 号：TB49[一般工业技术]