{"title":"求解单目标无约束优化问题的改进多普勒效应蝙蝠自适应声纳算法","authors":"N. Azlan, N. M. Yahya","doi":"10.1109/CSPA.2019.8696057","DOIUrl":null,"url":null,"abstract":"A modified adaptive bats sonar algorithm with Doppler Effect (MABSA-DE) is a new algorithm with an element of Doppler Effect theory that helped the transmitted bats’ beam towards a superior position. The performances of the proposed algorithm are validated on a several well-known single objective unconstrained benchmark test functions. The obtained results show that the algorithm can perform well to find an optimum solution. The statistical results of MABSA-DE to solve all the test functions also has been compared with the results from the original MABSA on similar test functions. The comparative study has shown that MABSA-DE outperforms the original algorithm, and thus, it can be an efficient alternative method in solving single objective unconstrained optimization problems.","PeriodicalId":400983,"journal":{"name":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Modified Adaptive Bats Sonar Algorithm with Doppler Effect Mechanism for Solving Single Objective Unconstrained Optimization Problems\",\"authors\":\"N. Azlan, N. M. Yahya\",\"doi\":\"10.1109/CSPA.2019.8696057\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A modified adaptive bats sonar algorithm with Doppler Effect (MABSA-DE) is a new algorithm with an element of Doppler Effect theory that helped the transmitted bats’ beam towards a superior position. The performances of the proposed algorithm are validated on a several well-known single objective unconstrained benchmark test functions. The obtained results show that the algorithm can perform well to find an optimum solution. The statistical results of MABSA-DE to solve all the test functions also has been compared with the results from the original MABSA on similar test functions. The comparative study has shown that MABSA-DE outperforms the original algorithm, and thus, it can be an efficient alternative method in solving single objective unconstrained optimization problems.\",\"PeriodicalId\":400983,\"journal\":{\"name\":\"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSPA.2019.8696057\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 15th International Colloquium on Signal Processing & Its Applications (CSPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSPA.2019.8696057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modified Adaptive Bats Sonar Algorithm with Doppler Effect Mechanism for Solving Single Objective Unconstrained Optimization Problems
A modified adaptive bats sonar algorithm with Doppler Effect (MABSA-DE) is a new algorithm with an element of Doppler Effect theory that helped the transmitted bats’ beam towards a superior position. The performances of the proposed algorithm are validated on a several well-known single objective unconstrained benchmark test functions. The obtained results show that the algorithm can perform well to find an optimum solution. The statistical results of MABSA-DE to solve all the test functions also has been compared with the results from the original MABSA on similar test functions. The comparative study has shown that MABSA-DE outperforms the original algorithm, and thus, it can be an efficient alternative method in solving single objective unconstrained optimization problems.