{"title":"基于混合蚁群优化和遗传算法的模因算法求解电容器最优布局","authors":"M. P. Pimentel Filho, M. F. Medeiros","doi":"10.1109/ISAP.2011.6082188","DOIUrl":null,"url":null,"abstract":"This paper aims to address the optimal allocation of capacitor banks in electric power distribution systems. Although it is not a new theme, and already well exploited, with many works have been published over the past 40 years, treating this subject, it aims to present an alternative to an exact treatment of the problem through the combined use of the peculiar characteristics of Metaheuristics, also includes a local search to improve the efficiency of global search and computational performance. In general, the methods described in the literature have advantages and limitations. The main idea is to join in a single algorithm, characteristics of methodologies already established, and working together to overcome individual limitations. With this objective, the here proposed algorithm uses the concepts of well established methods such as gradient, ant colony and genetic algorithms to solve the problem.","PeriodicalId":424662,"journal":{"name":"2011 16th International Conference on Intelligent System Applications to Power Systems","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A memetic algorithm based on mixed ant colony optimization and genetic algorithm for optimal capacitor placement\",\"authors\":\"M. P. Pimentel Filho, M. F. Medeiros\",\"doi\":\"10.1109/ISAP.2011.6082188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims to address the optimal allocation of capacitor banks in electric power distribution systems. Although it is not a new theme, and already well exploited, with many works have been published over the past 40 years, treating this subject, it aims to present an alternative to an exact treatment of the problem through the combined use of the peculiar characteristics of Metaheuristics, also includes a local search to improve the efficiency of global search and computational performance. In general, the methods described in the literature have advantages and limitations. The main idea is to join in a single algorithm, characteristics of methodologies already established, and working together to overcome individual limitations. With this objective, the here proposed algorithm uses the concepts of well established methods such as gradient, ant colony and genetic algorithms to solve the problem.\",\"PeriodicalId\":424662,\"journal\":{\"name\":\"2011 16th International Conference on Intelligent System Applications to Power Systems\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 16th International Conference on Intelligent System Applications to Power Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISAP.2011.6082188\",\"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 16th International Conference on Intelligent System Applications to Power Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISAP.2011.6082188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A memetic algorithm based on mixed ant colony optimization and genetic algorithm for optimal capacitor placement
This paper aims to address the optimal allocation of capacitor banks in electric power distribution systems. Although it is not a new theme, and already well exploited, with many works have been published over the past 40 years, treating this subject, it aims to present an alternative to an exact treatment of the problem through the combined use of the peculiar characteristics of Metaheuristics, also includes a local search to improve the efficiency of global search and computational performance. In general, the methods described in the literature have advantages and limitations. The main idea is to join in a single algorithm, characteristics of methodologies already established, and working together to overcome individual limitations. With this objective, the here proposed algorithm uses the concepts of well established methods such as gradient, ant colony and genetic algorithms to solve the problem.