期刊
KNOWLEDGE AND INFORMATION SYSTEMS
卷 58, 期 1, 页码 209-248出版社
SPRINGER LONDON LTD
DOI: 10.1007/s10115-018-1158-1
关键词
Symbiotic organisms search; Complex-valued encoding; Benchmark test functions; Engineering problems
资金
- National Science Foundation of China [61463007, 61563008]
- Project of Guangxi University for Nationalities Science Foundation [2016GXNSFAA380264]
Symbiotic organisms search algorithm is a new meta-heuristic algorithm based on the symbiotic relationship between the biological which was proposed in recent years. In this paper, a novel complex-valued encoding symbiotic organisms search (CSOS) algorithm is proposed. The algorithm introduces the idea of complex coding diploid. Each individual is composed of real and imaginary parts and extends the search space from one dimension to two dimensions. This increases the diversity of the population, further enhances the ability of the algorithm to find the global optimal value, and improves the precision of the algorithm. CSOS has been tested with 23 standard benchmark functions and 2 engineering design problems. The results show that CSOS has better ability of finding global optimal value and higher precision.
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