Pareto-Based Complete Local Search and Combined Timetabling for Multi-objective Job Shop Scheduling Problem with No-Wait Constraint  

作　　者：杨玉珍 顾幸生 

机构地区：[1]School of Electrical Engineering,Shanghai Dianji University [2]Key Laboratory of Advanced Control and Optimization for Chemical Process,Ministry of Education,East China University of Science and Technology

出　　处：《Journal of Donghua University(English Edition)》2016年第4期601-609,624,共10页东华大学学报（英文版）

基　　金：National Natural Science Foundations of China(Nos.61174040,61573144,11304200);Shanghai Commission of Science and Technology,China(No.12JC1403400);Shanghai Municipal Education Commission for Training Young Teachers,China(No.ZZSDJ15031);Shanghai Teaching and Reforming Experimental Undergraduate Majors Construction Program,China

摘　　要：Job shop scheduling has become the basis and core of advanced manufacturing technology. Various differences exist between academic research and practical production. The majority of previous researches on job shop scheduling problem (JSSP)describe the basic production environment, which have a single objective and limited constraints. However,a practical process of production is characterized by having multiple objectives,no-wait constraint,and limited storage. Thus this research focused on multiobjective,no-wait JSSP. To analyze the problem,it was further divided into two sub-problems, namely, sequencing and timetabling. Hybrid non-order strategy and modified complete local search with memory were used to solve each problem individually. A Pareto-based strategy for performing fitness assessment was presented in this study. Various experiments on benchmark problems proved the feasibility and effectiveness of the proposed algorithm.Job shop scheduling has become the basis and core of advanced manufacturing technology. Various differences exist between academic research and practical production. The majority of previous researches on job shop scheduling problem （JSSP）describe the basic production environment, which have a single objective and limited constraints. However,a practical process of production is characterized by having multiple objectives,no-wait constraint,and limited storage. Thus this research focused on multiobjective,no-wait JSSP. To analyze the problem,it was further divided into two sub-problems, namely, sequencing and timetabling. Hybrid non-order strategy and modified complete local search with memory were used to solve each problem individually. A Pareto-based strategy for performing fitness assessment was presented in this study. Various experiments on benchmark problems proved the feasibility and effectiveness of the proposed algorithm.

关 键 词：Pareto Scheduling scheduling constraints benchmark crossover fitness performing objectives sequencing 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]