Scheduling Algorithm Using Path Relinking for Production Process with Crane Interference

Author:

Tanizaki Takashi1ORCID,Yamada Kazuya1,Nakagawa Shigemasa2,Katagiri Hideki3ORCID

Affiliation:

1. Kindai University, 1 Takaya-Umenobe, Higashi-Hiroshima, Hiroshima 739-2116, Japan

2. NIPPON STEEL TEXENG. CO., LTD., Tokyo, Japan

3. Faculty of Engineering, Kanagawa University, Yokohama, Japan

Abstract

In manufacturing industries, customers demand a wide variety of products, with high quality and fast delivery. Production scheduling systems have become critical for efficient operation. However, scheduling problems in manufacturing are generally large and complex with many constraints. It is difficult to create an optimal production schedule that satisfies all constraints within a reasonable timeframe. This study targets a factory with multiple working machines and two overhead cranes. Our research aims to obtain a solution algorithm to avoid interference of overhead cranes and machine competition and a production plan that minimizes the total makespan for each job. As the problem must be solved within a reasonable timeframe, we have developed the solution algorithm using metaheuristics and scheduling simulation. In general, metaheuristic algorithms must strike a balance between an intensive search for good solutions and a search for diverse solutions. Accordingly, we propose a new algorithm using path relinking in a scatter search. This method was demonstrated to be effective in obtaining good solutions with little variation in numerical experiments. In this paper, we describe previous research, our target process, and new solution algorithm and discuss algorithm design methods based on computer experiments.

Publisher

Fuji Technology Press Ltd.

Subject

Industrial and Manufacturing Engineering,Mechanical Engineering

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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