{"title":"最佳人工蜂群算法","authors":"Harish Sharma, Sonal Sharma, Sandeep Kumar","doi":"10.1109/ICACCI.2016.7732158","DOIUrl":null,"url":null,"abstract":"Artificial Bee Colony (ABC) algorithm is the most popular add-on to class of swarm intelligence based meta-heuristic which is evolved to resolve the complex real world optimization problems. Most of the swarm intelligence based algorithms face the problem of stagnation, and premature convergence and ABC is not an exception. To reduce the chance of these problems as well as to control equilibrium between intensification and diversification capabilities of ABC, a unique variant of ABC is intended. In this intended variant, the employed bee stage, as well as onlooker bee stage of ABC algorithm is modified by taking inspiration from a local best candidate as well as the global best candidate. The intended ABC variant is named as Lbest Gbest ABC (LGABC) algorithm. The accuracy and efficiency of LGABC have examined over 12 benchmark functions and evaluated with the basic ABC, best so far ABC, Gbest ABC and Modified ABC and found that it may be an efficient contender in the field of swarm intelligence based algorithms.","PeriodicalId":371328,"journal":{"name":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","volume":"276 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Lbest Gbest Artificial Bee Colony algorithm\",\"authors\":\"Harish Sharma, Sonal Sharma, Sandeep Kumar\",\"doi\":\"10.1109/ICACCI.2016.7732158\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Artificial Bee Colony (ABC) algorithm is the most popular add-on to class of swarm intelligence based meta-heuristic which is evolved to resolve the complex real world optimization problems. Most of the swarm intelligence based algorithms face the problem of stagnation, and premature convergence and ABC is not an exception. To reduce the chance of these problems as well as to control equilibrium between intensification and diversification capabilities of ABC, a unique variant of ABC is intended. In this intended variant, the employed bee stage, as well as onlooker bee stage of ABC algorithm is modified by taking inspiration from a local best candidate as well as the global best candidate. The intended ABC variant is named as Lbest Gbest ABC (LGABC) algorithm. The accuracy and efficiency of LGABC have examined over 12 benchmark functions and evaluated with the basic ABC, best so far ABC, Gbest ABC and Modified ABC and found that it may be an efficient contender in the field of swarm intelligence based algorithms.\",\"PeriodicalId\":371328,\"journal\":{\"name\":\"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)\",\"volume\":\"276 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACCI.2016.7732158\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACCI.2016.7732158","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
摘要
人工蜂群(Artificial Bee Colony, ABC)算法是基于群智能的元启发式算法的一种最流行的补充,它是为解决复杂的现实优化问题而发展起来的。大多数基于群体智能的算法都面临着停滞的问题,过早收敛和ABC算法也不例外。为了减少出现这些问题的机会,并控制作业成本法集约化和多样化能力之间的平衡,我们打算采用一种独特的作业成本法。在这个拟变式中,ABC算法的受雇蜂阶段和旁观者蜂阶段分别从局部最优候选和全局最优候选中获得灵感进行了修改。预期的ABC变体被命名为Lbest Gbest ABC (LGABC)算法。通过对12个基准函数的检验,并对基本ABC、best so far ABC、Gbest ABC和Modified ABC进行了评价,发现LGABC在基于群体智能的算法领域可能是一个有效的竞争者。
Artificial Bee Colony (ABC) algorithm is the most popular add-on to class of swarm intelligence based meta-heuristic which is evolved to resolve the complex real world optimization problems. Most of the swarm intelligence based algorithms face the problem of stagnation, and premature convergence and ABC is not an exception. To reduce the chance of these problems as well as to control equilibrium between intensification and diversification capabilities of ABC, a unique variant of ABC is intended. In this intended variant, the employed bee stage, as well as onlooker bee stage of ABC algorithm is modified by taking inspiration from a local best candidate as well as the global best candidate. The intended ABC variant is named as Lbest Gbest ABC (LGABC) algorithm. The accuracy and efficiency of LGABC have examined over 12 benchmark functions and evaluated with the basic ABC, best so far ABC, Gbest ABC and Modified ABC and found that it may be an efficient contender in the field of swarm intelligence based algorithms.