An Optimization Algorithm Based on Brainstorming Process
An Optimization Algorithm Based on Brainstorming Process
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基于头脑风暴过程的优化算法
DOI：
10.4018/978-1-4666-6328-2.ch001
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发表时间：
2015-01-01
期刊：
影响因子：
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通讯作者：
Shi, Yuhui
中科院分区：
文献类型：
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作者：
Shi, Yuhui
在本章中，对人类头脑风暴过程进行了建模，并在此基础上介绍了头脑风暴优化（BSO）算法的两个版本。仿真结果表明，两种BSO算法在十个基准函数上都表现得相当好，这验证了所提出的BSO算法的有效性和实用性。仿真结果还表明，其中一种BSO算法——BSO - II，总体上比另一种BSO算法——BSO - I表现更好。此外，定义了平均簇间距离\(D_c\)和簇间多样性\(D_e\)，它们可用于衡量和监测迭代过程中簇质心的分布以及种群的信息熵。仿真结果说明，利用\(D_c\)所揭示的信息可以实现进一步的改进，这为BSO算法未来的研究指明了一个方向。
In this chapter, the human brainstorming process is modeled, based on which two versions of a Brain Storm Optimization (BSO) algorithm are introduced. Simulation results show that both BSO algorithms perform reasonably well on ten benchmark functions, which validates the effectiveness and usefulness of the proposed BSO algorithms. Simulation results also show that one of the BSO algorithms, BSO-II, performs better than the other BSO algorithm, BSO-I, in general. Furthermore, average inter-cluster distance D-c and inter-cluster diversity D-e are defined, which can be used to measure and monitor the distribution of cluster centroids and information entropy of the population over iterations. Simulation results illustrate that further improvement could be achieved by taking advantage of information revealed by D-c, which points at one direction for future research on BSO algorithms.