A series of most cited bio-inspired methods has been selected for this chapter. The order we chose for presenting the methods is also bio-inspired, in the sense that we go from invertebrates to vertebrates, and in the case of vertebrates, we start with water, then land, and finally air. A few benchmark functions have been selected for experimental testing (programs in MATLAB), which reveals slow or fast convergence in each of the methods. The methods considered are: Artificial Bee Colony (ABC), Firefly algorithm, Glowwarm Swarm Optimization algorithm, Krill Herd algorithm, Shuffled Frog Leaping algorithm (memetic evolution), Grey Wolf algorithm, bats, crow search, and cuckoo search.

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Evolutionary Optimization: Bio-inspired Methods

  • Jose Maria Giron-Sierra

摘要

A series of most cited bio-inspired methods has been selected for this chapter. The order we chose for presenting the methods is also bio-inspired, in the sense that we go from invertebrates to vertebrates, and in the case of vertebrates, we start with water, then land, and finally air. A few benchmark functions have been selected for experimental testing (programs in MATLAB), which reveals slow or fast convergence in each of the methods. The methods considered are: Artificial Bee Colony (ABC), Firefly algorithm, Glowwarm Swarm Optimization algorithm, Krill Herd algorithm, Shuffled Frog Leaping algorithm (memetic evolution), Grey Wolf algorithm, bats, crow search, and cuckoo search.