头脑风暴优化算法的综合调查

Shi Cheng, Yifei Sun, Junfeng Chen, Quande Qin, Xianghua Chu, Xiu-juan Lei, Yuhui Shi
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引用次数: 31

摘要

全面研究了一种新的群体智能算法——头脑风暴优化算法(BSO)的发展、实现、变体和未来发展方向。头脑风暴优化算法是一种模拟人类头脑风暴过程的新型群体智能算法。BSO中的个体通过收敛运算和发散运算在搜索空间/目标空间中进行分组和发散。据我们所知,BSO算法的开发与应用共发表论文75篇,论文8篇,专利5项。BSO算法中的每个个体不仅是待优化问题的解,而且是揭示问题全景的数据点。基于头脑风暴优化算法的发展,可以解决不同类型的优化问题和实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A comprehensive survey of brain storm optimization algorithms
The development, implementation, variant, and future directions of a new swarm intelligence algorithm, brain storm optimization (BSO) algorithm, are comprehensively surveyed. Brain storm optimization algorithm is a new and promising swarm intelligence algorithm, which simulates the human brainstorming process. Through the convergent operation and divergent operation, individuals in BSO are grouped and diverged in the search space/objective space. To the best of our knowledge, there are 75 papers, 8 theses, and 5 patents in total on the development and application of the BSO algorithm. Every individual in the BSO algorithm is not only a solution to the problem to be optimized, but also a data point to reveal the landscape of the problem. Based on the developments of brain storm optimization algorithms, different kinds of optimization problems and real-world applications could be solved.
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