Flexible job shop scheduling with lot streaming based on improved migrating birds optimization algorithm

被引：0

作者：

Liu, Xuehong ^{[1
,2
]}

Duan, Cheng ^{[1
]}

Wang, Lei ^{[1
,2
]}

机构：

[1] School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan,430070, China

[2] Hubei Provincial Digital Manufacturing Key Laboratory, Wuhan,430070, China

来源：

Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2021年 / 27卷 / 11期

基金：

中国国家自然科学基金;

关键词：

Production efficiency - Job shop scheduling;

D O I：

10.13196/j.cims.2021.11.012

中图分类号：

学科分类号：

摘要：

The scheduling strategy of variable sublots is an effective method to improve the production efficiency of large-scale flexible job shop and the utilization rate of equipment. Aiming at the characteristics of Flexible Job-Shop Scheduling Problem with Variable Sublots (FJSP-VS), a multi-objective flexible job shop scheduling model with minimizing the completion time and the sublots number was established, and a disjunctive graph model for the problem was also established. An Improved Migrating Birds Optimization (IMBO) algorithm was proposed to solve the problem. In this algorithm, two strategies of the elite batch division and the feasible neighboring structures were designed to improve the search efficiency. The advantages of variable sublots and the effectiveness of the proposed algorithm were proved by comparative experiments. © 2021, Editorial Department of CIMS. All right reserved.

引用

页码：3185 / 3195

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