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

ISSN号：1673-6540
期刊名称：《电机与控制应用》
时间：0
分类：TP278[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
作者机构：[1]School of Electrical Engineering, Shanghai Dianji University, Shanghai 201306, China, [2]Key Laboratory of Advanced Control and Optimization for Chemical Process, Ministry of Education, East China University ofScience and Technology, Shanghai 200237, China
相关基金：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

作者：杨玉珍[1], 顾幸生[2]

关键词： job, shop, scheduling, NO-WAIT, TIMETABLING, MULTI-OBJECTIVE, Pareto Scheduling scheduling constraints benchmark crossover fitness performing objectives sequencing

中文摘要：

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.

英文摘要：

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.

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