Structure of Multi-Stage Composite Genetic Algorithm (MSC-GA) and its performance

Abstract

In view of the slowness and the locality of convergence for Simple Genetic Algorithm (SGA) in solving complex optimization problems, we propose an improved genetic algorithm named Multi-Stage Composite Genetic Algorithm (MSC-GA) through reducing the optimization-search range gradually, and the structure and implementation steps ofMSC-GA is also discussed. Then, we consider its global convergence under the elitist preserving strategy using the Markov chain theory and analyze its performance through three examples from different aspects. The results indicate that the new algorithm possesses several advantages such as better convergence and less chance of being trapped into premature states. As a result, it can be widely applied to many large-scale optimization problems which require higher accuracy. 2011 Elsevier Ltd. All rights reserved.

DOI: 10.1016/j.eswa.2011.01.110

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Cite this paper

@article{Li2011StructureOM, title={Structure of Multi-Stage Composite Genetic Algorithm (MSC-GA) and its performance}, author={Fachao Li and Lida Xu and Chenxia Jin and Hong Wang}, journal={Expert Syst. Appl.}, year={2011}, volume={38}, pages={8929-8937} }