An Adaptive Distributed Size Wolf Pack Optimization Algorithm Using Strategy of Jumping for Raid(September 2018)
作者： Dongxing Wang , Xu Qian , Kang Liu , Xiaojuan Ban , Xinyu Guan
DOI: 10.1109/ACCESS.2018.2878520
关键词:
摘要: On the premise of guaranteeing accuracy solution, to reduce time spent for optimization by an existing algorithm named adaptive shrinking grid search chaos wolf (ASGS-CWOA), distribution size (ADS) pack using strategy jumping raid (for short: WDX-WPOA) was proposed. First, is proposed improve performance in raiding process airlifting directly half wolves be around leader that can accelerate convergence algorithm; Moreover, ADS used distribute specific locations according its rules, so as enhance probability finding optical value. Under same condition, results numerical experiments demonstrate WDX-WPOA possesses preferable ability including best global accuracy, better robustness, and fast speed compared with classical genetic algorithm, particle swarm LWPS, CWOA; especially, has than ASGS-CWOA prerequisite solution quality.
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