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Spherical evolution for solving continuous optimization problems
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DOI：10.1016/j.asoc.2019.105499.png)
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Abstract
En 中文
In these years, more and more nature-inspired meta-heuristic algorithms have been proposed; search operators have been their core problem. The common characteristics or mechanism of search operators in different algorithms have not been represented by a standard format. In this paper, we first propose the concept of a search pattern and a search style represented by a mathematical model. Second, we propose a new search style, namely a spherical search style, inspired by the traditional hypercube search style. Furthermore, a spherical evolution algorithm is proposed based on the search pattern and spherical search style. At the end, 30 benchmark functions of CEC2017 and a real-world optimization problem are tested. Experimental results and analysis demonstrate that the proposed method consistently outperforms other state-of-the-art algorithms. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Differential evolution
Spherical evolution
Search pattern
Spherical search style
Data clustering optimization
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