Sandeep Kumar, Ashutosh Kumar, V. Sharma, Harish Sharma
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引用次数: 11
摘要
人工蜂群算法(ABC)是一种自然启发算法(NIA)。ABC的动机是蜜蜂聪明的觅食行为。与其他基于种群的随机算法相比,ABC算法在局部搜索原因的探索和搜索空间中最优可能解的开发上也缺乏平衡。该算法是两种模因算法的混合;它结合了ABC中的利维飞行搜索(LFABC)和ABC中的模因搜索(MeABC)算法。该算法被命名为Levy Flight Memetic Search in ABC (LFMABC)算法。为了证明LFMABC算法优于ABC算法及其最新变体,本文在11个基准函数和两个实际问题上对LFMABC算法进行了测试。结果表明,所提出的LFMABC策略能够在较短的时间内找到最优解。
A novel hybrid memetic search in Artificial Bee Colony algorithm
Artificial Bee Colony (ABC) algorithm is a Nature Inspired Algorithm (NIA). ABC is motivated by clever food foraging behavior of honey bees. Comparable to other population based stochastic algorithm ABC also lack balance in exploration of local search reason and exploitation of finest possible solutions in search space. The proposed algorithm is a hybrid of two memetic algorithms; it combines Levy Flight search in ABC (LFABC) and Memetic Search in ABC (MeABC) algorithm. The proposed algorithm named as Levy Flight Memetic Search in ABC (LFMABC) algorithm. The proposed LFMABC algorithm is tested over eleven benchmark functions in addition to two real world problems in order to establish its superiority over ABC and its recent variants. Results shows that proposed strategy LFMABC is able to find optimum in less time for considered problems.