Research on the scheduling of steel mesh production line based on the improved grey wolf algorithm

Author:

Yin Haibin,Feng Yu,Xie Junyong,Zhou Xiangqun,Zhang Yushun,Shi Dongxing,Li Zhongwei

Abstract

Abstract To solve the scheduling problem of a flexible production line of reinforced mesh, a mathematical model of flexible production line scheduling of reinforced mesh was established to minimize the maximum completion time. The Improved Gray Wolf Algorithm (IGWO) was designed, and the improvement measures of the Gray Wolf Algorithm (GWO) were proposed from the population initialization method, key parameter improvement, and search mechanism. Through the example verification, the Improved Grey Wolf Algorithm is applied to the scheduling problem of the flexible steel production line. The problem of the flexible production line of steel mesh and the results of the Improved Grey Wolf Algorithm, Grey Wolf Algorithm, Genetic Algorithm (GA), and artificial scheduling are compared. The results verify that the results of the enhanced Grey Wolf Algorithm have better quality and can better guide the production line to carry out efficient and energy-saving production.

Publisher

IOP Publishing

Reference11 articles.

1. Minimising makespan in the two-stage assembly hybrid flow shop scheduling problem using artificial immune systems [J];Komaki;International Journal of Production Research,2016

2. An improved multi-objective grey Wolf optimisation algorithm for fuzzy blocking flow shop scheduling problem (Conference Paper) [A];Yang,2017

3. Grey Wolf Optimizer algorithm for the two-stage assembly flow shop scheduling problem with release time [J];Komaki;Journal of Computational Science,2015

4. Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective [J];Imma;COMPUTERS & OPERATIONS RESEARCH,2010

5. Chaos-enhanced synchronised bat optimizer [J];He-long;Applied Mathematical Modelling,2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3