The genetic algorithm with two point crossover to solve the resource-constrained project scheduling problems

Hela Ouerfelli, A. Dammak
{"title":"The genetic algorithm with two point crossover to solve the resource-constrained project scheduling problems","authors":"Hela Ouerfelli, A. Dammak","doi":"10.1109/ICMSAO.2013.6552686","DOIUrl":null,"url":null,"abstract":"In the last few decades, the resource-constrained project-scheduling problem has become the key of the success of researching project in the enterprises and has become a popular problem type in operations research. However, due to its strongly NP-hard status, the effectiveness of exact optimization procedures is restricted to relatively small instances. In this paper, we present a genetic algorithm (GA), the so called genetic algorithm with two-point crossover (GA2P), for this problem that is able to provide near-optimal heuristic solutions. A full factorial computational experiment was set up using the well-known standard instances in PSPLIB, and the results reveal that the algorithm is effective for the RCPSP.","PeriodicalId":339666,"journal":{"name":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSAO.2013.6552686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

In the last few decades, the resource-constrained project-scheduling problem has become the key of the success of researching project in the enterprises and has become a popular problem type in operations research. However, due to its strongly NP-hard status, the effectiveness of exact optimization procedures is restricted to relatively small instances. In this paper, we present a genetic algorithm (GA), the so called genetic algorithm with two-point crossover (GA2P), for this problem that is able to provide near-optimal heuristic solutions. A full factorial computational experiment was set up using the well-known standard instances in PSPLIB, and the results reveal that the algorithm is effective for the RCPSP.
采用两点交叉的遗传算法求解资源受限的工程调度问题
近几十年来,资源约束下的项目调度问题已成为企业项目研究成功与否的关键问题,成为运筹学研究中的热门问题类型。然而,由于其强烈的NP-hard状态,精确优化过程的有效性仅限于相对较小的实例。本文针对这一问题,提出了一种能够提供近似最优启发式解的遗传算法(GA),即两点交叉遗传算法(GA2P)。利用PSPLIB中众所周知的标准实例建立了全析因计算实验,结果表明该算法对RCPSP是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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