柔性制造系统中机械和物料搬运设备集成调度的多目标蚁群算法

T. Yung, S. Ponnambalam, M. Yogeswaran
{"title":"柔性制造系统中机械和物料搬运设备集成调度的多目标蚁群算法","authors":"T. Yung, S. Ponnambalam, M. Yogeswaran","doi":"10.1109/COASE.2009.5234130","DOIUrl":null,"url":null,"abstract":"A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.","PeriodicalId":386046,"journal":{"name":"2009 IEEE International Conference on Automation Science and Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Multi-objective ACO for integrated scheduling of machines and material handling equipment in flexible manufacturing systems\",\"authors\":\"T. Yung, S. Ponnambalam, M. Yogeswaran\",\"doi\":\"10.1109/COASE.2009.5234130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.\",\"PeriodicalId\":386046,\"journal\":{\"name\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COASE.2009.5234130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2009.5234130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

研究了自动化制造系统中机器和物料搬运设备的多目标集成调度问题。FMS环境是由6台多操作机器和2台自动导引车(agv)组成的。提出了一种蚁群优化算法,以最大化机器利用率、最大化利润、最小化AGV行驶时间和最小化AGV能量利用率为目标,对多目标函数进行优化。将所提出的蚁群算法与传统的优先级调度规则(pdrs)进行了性能比较,发现所提出的蚁群算法的性能优于所考虑的优先级调度规则。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-objective ACO for integrated scheduling of machines and material handling equipment in flexible manufacturing systems
A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信