A constructive search algorithm for combinatorial dynamic optimization problems

A. Baykasoğlu, F. Özsoydan
{"title":"A constructive search algorithm for combinatorial dynamic optimization problems","authors":"A. Baykasoğlu, F. Özsoydan","doi":"10.1109/EAIS.2015.7368783","DOIUrl":null,"url":null,"abstract":"In most of the optimization studies, the problem related data is assumed to be exactly known beforehand and remain stationary throughout whole optimization process. However, majority of real life problems and their practical applications are dynamic in their nature due to the reasons arising from unpredictable events, such as rush orders, fluctuating capacities of manufacturing constraints, changes in costs or profits. A problem, carrying one of these features is known as dynamic optimization problem (DOP) in the related literature. In DOPs the aim is not only to find the optimum of the current problem configuration, but to keep track of the moving optima. Dynamic optimization is a hot research area and a notable variety of solution methodologies are developed for DOPs in the past decade. As a contribution to the existing literature of DOPs, in the current work, the idea of using a multi-start and constructive search algorithm and thus breaking the dependency to the previously found solutions is presented. The performance tests are conducted on the generalized assignment problem, which has numerous real life applications. In regard to the obtained results, the proposed method is found promising.","PeriodicalId":325875,"journal":{"name":"2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EAIS.2015.7368783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

In most of the optimization studies, the problem related data is assumed to be exactly known beforehand and remain stationary throughout whole optimization process. However, majority of real life problems and their practical applications are dynamic in their nature due to the reasons arising from unpredictable events, such as rush orders, fluctuating capacities of manufacturing constraints, changes in costs or profits. A problem, carrying one of these features is known as dynamic optimization problem (DOP) in the related literature. In DOPs the aim is not only to find the optimum of the current problem configuration, but to keep track of the moving optima. Dynamic optimization is a hot research area and a notable variety of solution methodologies are developed for DOPs in the past decade. As a contribution to the existing literature of DOPs, in the current work, the idea of using a multi-start and constructive search algorithm and thus breaking the dependency to the previously found solutions is presented. The performance tests are conducted on the generalized assignment problem, which has numerous real life applications. In regard to the obtained results, the proposed method is found promising.
组合动态优化问题的构造搜索算法
在大多数优化研究中,假设与问题相关的数据事先是准确已知的,并且在整个优化过程中保持平稳。然而,现实生活中的大多数问题及其实际应用在本质上是动态的,原因是不可预测的事件,如紧急订单、制造限制的能力波动、成本或利润的变化。带有这些特征之一的问题在相关文献中被称为动态优化问题(DOP)。在DOPs中,目标不仅是找到当前问题配置的最优,而且要跟踪移动的最优。动态优化是一个热门的研究领域,在过去的十年中,人们开发了各种各样的动态优化方法。作为对现有DOPs文献的贡献,在当前的工作中,提出了使用多启动和建设性搜索算法的想法,从而打破了对先前找到的解决方案的依赖。对具有大量实际应用的广义分配问题进行了性能测试。根据所得到的结果,发现所提出的方法是有前途的。
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