{"title":"细菌觅食优化算法:一种无导数技术","authors":"Nitin Kumar Jhankal, D. Adhyaru","doi":"10.1109/NUICONE.2011.6153240","DOIUrl":null,"url":null,"abstract":"Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for optimization and control. BFOA is inspired by the social foraging behaviour of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. In present paper, a detailed explanation of this algorithm is given. Comparative analysis of BFOA with Genetic Algorithm (GA) is presented.","PeriodicalId":206392,"journal":{"name":"2011 Nirma University International Conference on Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Bacterial foraging optimization algorithm: A derivative free technique\",\"authors\":\"Nitin Kumar Jhankal, D. Adhyaru\",\"doi\":\"10.1109/NUICONE.2011.6153240\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for optimization and control. BFOA is inspired by the social foraging behaviour of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. In present paper, a detailed explanation of this algorithm is given. Comparative analysis of BFOA with Genetic Algorithm (GA) is presented.\",\"PeriodicalId\":206392,\"journal\":{\"name\":\"2011 Nirma University International Conference on Engineering\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Nirma University International Conference on Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NUICONE.2011.6153240\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Nirma University International Conference on Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NUICONE.2011.6153240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Bacterial foraging optimization algorithm: A derivative free technique
Bacterial foraging optimization algorithm (BFOA) has been widely accepted as a global optimization algorithm of current interest for optimization and control. BFOA is inspired by the social foraging behaviour of Escherichia coli. BFOA has already drawn the attention of researchers because of its efficiency in solving real-world optimization problems arising in several application domains. In present paper, a detailed explanation of this algorithm is given. Comparative analysis of BFOA with Genetic Algorithm (GA) is presented.
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