DOI: 10.1016/J.CNSNS.2013.08.027
关键词: Mating 、 Benchmark (computing) 、 Genetic algorithm 、 Continuous optimization 、 Artificial intelligence 、 Computer science 、 Optimization problem 、 Evolutionary algorithm 、 Optimization algorithm
摘要: Abstract Thanks to their simplicity and flexibility, evolutionary algorithms (EAs) have attracted significant attention tackle complex optimization problems. The underlying idea behind all EAs is the same they differ only in technical details. In this paper, we propose a novel version of EAs, bird mating optimizer (BMO), for continuous problems which inspired by strategies species during season. BMO imitates behavior metaphorically breed broods with superior genes designing optimum searching techniques. On large set unimodal multimodal benchmark functions, represents competitive performance other EAs.