{"title":"摇-弑君:进化算法多样性控制的新启发式","authors":"J. Ramírez, M. Rivera, A. Hernandez-Aguirre","doi":"10.1109/MICAI.2007.9","DOIUrl":null,"url":null,"abstract":"Evolutionary algorithms have been very successful at solving global optimization problems. Two competing goals govern the performance of evolutionary algorithms: exploration and exploitation. This paper proposes a new heuristic to keep population diversity: the shake and the regicide. The shake heuristic improves the exploration by perturbing the whole population. The regicide heuristic (kill the leader) reduces the risk of being, early, trapped by a local minimum. Experiments demonstrate that the Shake-Regicide heuristic improves significantly the precision of the results (in about 3 orders of magnitude) of standard differential evolution, genetic algorithm and evolution strategy.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shake – Regicide: A New Heuristic for the Diversity Control of Evolutionary Algorithms\",\"authors\":\"J. Ramírez, M. Rivera, A. Hernandez-Aguirre\",\"doi\":\"10.1109/MICAI.2007.9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Evolutionary algorithms have been very successful at solving global optimization problems. Two competing goals govern the performance of evolutionary algorithms: exploration and exploitation. This paper proposes a new heuristic to keep population diversity: the shake and the regicide. The shake heuristic improves the exploration by perturbing the whole population. The regicide heuristic (kill the leader) reduces the risk of being, early, trapped by a local minimum. Experiments demonstrate that the Shake-Regicide heuristic improves significantly the precision of the results (in about 3 orders of magnitude) of standard differential evolution, genetic algorithm and evolution strategy.\",\"PeriodicalId\":296192,\"journal\":{\"name\":\"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)\",\"volume\":\"69 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-11-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MICAI.2007.9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICAI.2007.9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Shake – Regicide: A New Heuristic for the Diversity Control of Evolutionary Algorithms
Evolutionary algorithms have been very successful at solving global optimization problems. Two competing goals govern the performance of evolutionary algorithms: exploration and exploitation. This paper proposes a new heuristic to keep population diversity: the shake and the regicide. The shake heuristic improves the exploration by perturbing the whole population. The regicide heuristic (kill the leader) reduces the risk of being, early, trapped by a local minimum. Experiments demonstrate that the Shake-Regicide heuristic improves significantly the precision of the results (in about 3 orders of magnitude) of standard differential evolution, genetic algorithm and evolution strategy.