求解多目标优化问题的萤火虫群算法

2013 Ninth International Conference on Computational Intelligence and Security Pub Date : 2013-12-14 DOI:10.1109/CIS.2013.10

He Deng-xu, Liu Gui-qing, Zhu Hua-zheng

{"title":"求解多目标优化问题的萤火虫群算法","authors":"He Deng-xu, Liu Gui-qing, Zhu Hua-zheng","doi":"10.1109/CIS.2013.10","DOIUrl":null,"url":null,"abstract":"The glowworm swarm optimization algorithm is used to solve multi-objective optimization problem (MOP-GSO). It is shown by simulation that, MOP-GSO algorithm is effective to solve multi-objective optimization. Compared with NSGA2, it is better in term of the spread of the solutions.","PeriodicalId":294223,"journal":{"name":"2013 Ninth International Conference on Computational Intelligence and Security","volume":"82 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Glowworm Swarm Optimization Algorithm for Solving Multi-objective Optimization Problem\",\"authors\":\"He Deng-xu, Liu Gui-qing, Zhu Hua-zheng\",\"doi\":\"10.1109/CIS.2013.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The glowworm swarm optimization algorithm is used to solve multi-objective optimization problem (MOP-GSO). It is shown by simulation that, MOP-GSO algorithm is effective to solve multi-objective optimization. Compared with NSGA2, it is better in term of the spread of the solutions.\",\"PeriodicalId\":294223,\"journal\":{\"name\":\"2013 Ninth International Conference on Computational Intelligence and Security\",\"volume\":\"82 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Ninth International Conference on Computational Intelligence and Security\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.2013.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Ninth International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2013.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 7

摘要

采用萤火虫群优化算法求解多目标优化问题。仿真结果表明，MOP-GSO算法是解决多目标优化问题的有效方法。与NSGA2相比，溶液的扩散效果更好。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Glowworm Swarm Optimization Algorithm for Solving Multi-objective Optimization Problem

The glowworm swarm optimization algorithm is used to solve multi-objective optimization problem (MOP-GSO). It is shown by simulation that, MOP-GSO algorithm is effective to solve multi-objective optimization. Compared with NSGA2, it is better in term of the spread of the solutions.

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

2013 Ninth International Conference on Computational Intelligence and Security

自引率

0.00%

发文量