{"title":"正弦优化算法(SOA):一种利用正弦余弦算法中搜索主体改变更新位置策略的优化算法","authors":"Mostafa Meshkat, Mohsen Parhizgar","doi":"10.1109/ICSPIS.2017.8311581","DOIUrl":null,"url":null,"abstract":"In this paper, the update position of search agent strategy in Sine Cosine Algorithm (SCA) is replaced with a new update position strategy. In this strategy, the update position of each search agent is determined randomly by the search agent with the best position or the position of a random search agent. Moreover, contrary to SCA, this strategy merely uses sine function. That is why the proposed method is called Sine Optimization Algorithm (SOA). The performance of SOA and SCA was evaluated over a set of benchmark functions. The results show that SOA enjoys a higher accuracy to reach the global best compared with SCA, while also having a higher convergence speed.","PeriodicalId":380266,"journal":{"name":"2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS)","volume":"38 11","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Sine Optimization Algorithm (SOA): A novel optimization algorithm by change update position strategy of search agent in Sine Cosine Algorithm\",\"authors\":\"Mostafa Meshkat, Mohsen Parhizgar\",\"doi\":\"10.1109/ICSPIS.2017.8311581\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the update position of search agent strategy in Sine Cosine Algorithm (SCA) is replaced with a new update position strategy. In this strategy, the update position of each search agent is determined randomly by the search agent with the best position or the position of a random search agent. Moreover, contrary to SCA, this strategy merely uses sine function. That is why the proposed method is called Sine Optimization Algorithm (SOA). The performance of SOA and SCA was evaluated over a set of benchmark functions. The results show that SOA enjoys a higher accuracy to reach the global best compared with SCA, while also having a higher convergence speed.\",\"PeriodicalId\":380266,\"journal\":{\"name\":\"2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS)\",\"volume\":\"38 11\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSPIS.2017.8311581\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd Iranian Conference on Intelligent Systems and Signal Processing (ICSPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSPIS.2017.8311581","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sine Optimization Algorithm (SOA): A novel optimization algorithm by change update position strategy of search agent in Sine Cosine Algorithm
In this paper, the update position of search agent strategy in Sine Cosine Algorithm (SCA) is replaced with a new update position strategy. In this strategy, the update position of each search agent is determined randomly by the search agent with the best position or the position of a random search agent. Moreover, contrary to SCA, this strategy merely uses sine function. That is why the proposed method is called Sine Optimization Algorithm (SOA). The performance of SOA and SCA was evaluated over a set of benchmark functions. The results show that SOA enjoys a higher accuracy to reach the global best compared with SCA, while also having a higher convergence speed.