{"title":"基于和谐搜索和入侵杂草优化的高效混合算法","authors":"Aijia Ouyang, Zhiguo Yang","doi":"10.1109/FSKD.2016.7603169","DOIUrl":null,"url":null,"abstract":"Considering that invasive weed optimization (IWO) algorithm and the harmony search (HS) algorithm easily plunge into local optimal solution with low computing precision when they are applied to solve complex function problems, this paper improves the IWO algorithm and the HS algorithm. We introduce some strategies such as fixing the number of seeds, reinitializing boundary solutions, multi-individual global HS, and parameter optimization, etc. In order to make full use of the advantages of two algorithms, they are mixed in this paper, whereby the IWO algorithm based on HS is put forward, which is called HS-IWO for short. Through tests on 10 complex functions, the experimental results verify the accuracy, efficiency and stabilization of the HS-IWO algorithm.","PeriodicalId":373155,"journal":{"name":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"An efficient hybrid algorithm based on harmony search and invasive weed optimization\",\"authors\":\"Aijia Ouyang, Zhiguo Yang\",\"doi\":\"10.1109/FSKD.2016.7603169\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Considering that invasive weed optimization (IWO) algorithm and the harmony search (HS) algorithm easily plunge into local optimal solution with low computing precision when they are applied to solve complex function problems, this paper improves the IWO algorithm and the HS algorithm. We introduce some strategies such as fixing the number of seeds, reinitializing boundary solutions, multi-individual global HS, and parameter optimization, etc. In order to make full use of the advantages of two algorithms, they are mixed in this paper, whereby the IWO algorithm based on HS is put forward, which is called HS-IWO for short. Through tests on 10 complex functions, the experimental results verify the accuracy, efficiency and stabilization of the HS-IWO algorithm.\",\"PeriodicalId\":373155,\"journal\":{\"name\":\"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FSKD.2016.7603169\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FSKD.2016.7603169","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An efficient hybrid algorithm based on harmony search and invasive weed optimization
Considering that invasive weed optimization (IWO) algorithm and the harmony search (HS) algorithm easily plunge into local optimal solution with low computing precision when they are applied to solve complex function problems, this paper improves the IWO algorithm and the HS algorithm. We introduce some strategies such as fixing the number of seeds, reinitializing boundary solutions, multi-individual global HS, and parameter optimization, etc. In order to make full use of the advantages of two algorithms, they are mixed in this paper, whereby the IWO algorithm based on HS is put forward, which is called HS-IWO for short. Through tests on 10 complex functions, the experimental results verify the accuracy, efficiency and stabilization of the HS-IWO algorithm.