A New Hybrid Optimization Algorithm Framework to Solve Constrained Optimization Problem

Authors:
Huang Zhangcan;Cheng Hao
Affiliations:
School of Science, Wuhan University of Technology, Wuhan 430070, China;School of Mechanical and Electrical Engineering, Wuhan University of Technology, Wuhan 430070, China
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Year:
2007

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Abstract

Evolutionary Computation made great success from the theory of natural selection devised by Charles Darwin. It was a process of randomly searching but not emphasizing each individuals respective functions. This paper proposed a hybrid optimization algorithm framework trying to incorporate natural selection and survival of the fittest and birds of a feather flock together. Aiming at balancing search results and search speed, we adopted the search strategy to classify the individuals by their fitness. Individuals classification differentiated respective function in search process, thats the excellent individuals mine the local optimal solution and others explore the search domain to find new local optimal solution. Experimental findings support the theoretical basis of the proposed framework.