Title: Review of meta-heuristics and generalised evolutionary walk algorithm

Authors: Xin-She Yang

Addresses: Mathematics and Scientific Computing, National Physical Laboratory, Teddington, TW11 0LW, UK

Abstract: Meta-heuristic algorithms are often nature-inspired, and they are becoming very powerful in solving global optimisation problems. More than a dozen major meta-heuristic algorithms have been developed over the last three decades, and there exist even more variants and hybrids of meta-heuristics. This paper intends to provide an overview of nature-inspired meta-heuristic algorithms, from a brief history to their applications. We try to analyse the main components of these algorithms and how and why they work. Then, we intend to provide a unified view of meta-heuristics by proposing a generalised evolutionary walk algorithm (GEWA). Finally, we discuss some of the important open questions.

Keywords: cuckoo search; differential evolution; firefly algorithm; genetic algorithms; GAs; nature-inspired metaheuristics; bio-inspired computation; generalised evolutionary walk algorithm.

DOI: 10.1504/IJBIC.2011.039907

International Journal of Bio-Inspired Computation, 2011 Vol.3 No.2, pp.77 - 84

Published online: 12 Nov 2014 *

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