DocumentCode :
238598
Title :
An inter-molecular adaptive collision scheme for Chemical Reaction Optimization
Author :
Yu, James J. Q. ; Li, Victor O. K. ; Lam, Albert Y. S.
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
1998
Lastpage :
2004
Abstract :
Optimization techniques are frequently applied in science and engineering research and development. Evolutionary algorithms, as a kind of general-purpose metaheuristic, have been shown to be very effective in solving a wide range of optimization problems. A recently proposed chemical-reaction-inspired metaheuristic, Chemical Reaction Optimization (CRO), has been applied to solve many global optimization problems. However, the functionality of the inter-molecular ineffective collision operator in the canonical CRO design overlaps that of the on-wall ineffective collision operator, which can potential impair the overall performance. In this paper we propose a new inter-molecular ineffective collision operator for CRO for global optimization. To fully utilize our newly proposed operator, we also design a scheme to adapt the algorithm to optimization problems with different search space characteristics. We analyze the performance of our proposed algorithm with a number of widely used benchmark functions. The simulation results indicate that the new algorithm has superior performance over the canonical CRO.
Keywords :
evolutionary computation; CRO design; canonical CRO; chemical reaction optimization; chemical-reaction-inspired metaheuristic; collision; evolutionary algorithms; global optimization problems; inter-molecular adaptive collision scheme; inter-molecular ineffective collision operator; optimization techniques; Algorithm design and analysis; Benchmark testing; Chemicals; Optimization; Simulation; Sociology; Statistics; Chemical reaction optimization; evolutionary computation; global optimization; inter-molecular operator; meta-heuristic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
Type :
conf
DOI :
10.1109/CEC.2014.6900234
Filename :
6900234
Link To Document :
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