摘要
Bio-inspired optimization algorithms[1,2]are a set of optimization algorithms inspired by natural phenomena,such as evolutionary processes,social behaviours,and swarm intelligence[3].These algorithms attempt to simulate these processes to solve optimization problems[4,5].Classical bio-inspired algorithms include genetic algorithm,ant colony optimization,artificial bee colony,particle swarm optimization,firefly algorithm,Japanese tree frog algorithm,Harris hawks optimization[6],slime mould algorithm[7],grey wolf optimization,sparrow search algorithm,whale optimization algorithm,etc.Fig.1 shows the taxonomy of common bio-inspired optimization algorithms.There are some recent newly proposed bio-inspired algorithms,such as Siberian tiger optimization[8],jellyfish search algorithm[9],etc.
