Triangle Evolution--A Hybrid Heuristic for Global Optimization |
Received:March 19, 2007 Revised:March 24, 2007 |
Key Words:
global optimization evolutionary computation differential evolution simplex method.
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Fund Project:the National Natural Science Foundation of China (No.10671029). |
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Abstract: |
This paper presents a hybrid heuristic--triangle evolution (TE) for global optimization. It is a real coded evolutionary algorithm. As in differential evolution (DE), TE targets each individual in current population and attempts to replace it by a new better individual. However, the way of generating new individuals is different. TE generates new individuals in a Nelder-Mead way, while the simplices used in TE is 1 or 2 dimensional. The proposed algorithm is very easy to use and efficient for global optimization problems with continuous variables. Moreover, it requires only one (explicit) control parameter. Numerical results show that the new algorithm is comparable with DE for low dimensional problems but it outperforms DE for high dimensional problems. |
Citation: |
DOI:10.3770/j.issn:1000-341X.2009.02.006 |
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