一种新的基于群的优化算法

Fevzi Tugrul Varna, P. Husbands
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引用次数: 0

摘要

提出了一种新的基于群体的搜索算法:生物育种智能群体(BIS)算法。BIS制剂模仿动物典型生命周期的后代和成熟阶段。与本质一样,BIS算法在代理之间进行性别区分,主要搜索策略利用男性代理之间的竞争,试图为女性提供更好的位置。BIS代理采用各种受自然启发的交配策略,生殖模型的灵感来自于温度依赖性性别决定(TSD),这是一种爬行动物的生殖系统。BIS算法中受TSD启发的繁殖模型使雌性智能体能够根据雄性伴侣提供的指导来控制后代的性别,从而调节群体中的男女比例,从而自动控制智能体群体内探索和开发的平衡。BIS算法的效率在广泛的基准测试中得到了测试,包括无约束的高维和现实世界的问题。与许多领先的基于种群的随机搜索方法相比,BIS算法表现非常好,找到了最多数量的全局最优。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
BIS: A New Swarm-Based Optimisation Algorithm
This paper presents a novel swarm-based search algorithm: the bio-breeding intelligent swarm (BIS) algorithm. BIS agents imitate the offspring and maturity phases of the typical lifecycle of an animal. As in nature, the BIS algorithm makes gender distinction among agents and the main search strategy exploits competition between male agents in an attempt to provide a better location for females. BIS agents embark on various nature-inspired mating strategies and the inspiration for the reproduction model is derived from temperature-dependent sex determination (TSD), a reptilian reproduction system. The BIS algorithm’s TSD inspired reproduction model enables female agents to control the gender of offsprings based on guidance provided by their male mates, subsequently resulting in regulation of the male-female ratio in the swarm which in turn auto-controls the balance of exploration and exploitation within the population of agents. The efficiency of the BIS algorithm was tested over a wide range of benchmarks including unconstrained high dimensional and real-world problems. The BIS algorithm performed very well in comparison with a number of leading population-based stochastic search methods, finding the highest number of global optimums.
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