%0 Report %D 2013 %T Benchmark Functions for CEC'2013 Special Session and Competition on Niching Methods for Multimodal Function Optimization' %A Xiaodong Li %A Andries Engelbrecht %A M. G. Epitropakis %I Evolutionary Computation and Machine Learning Group, RMIT University %C Melbourne, Australia %G eng %U http://goanna.cs.rmit.edu.au/~xiaodong/cec13-niching/competition/ %0 Conference Paper %B IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence) %D 2008 %T Balancing the exploration and exploitation capabilities of the Differential Evolution Algorithm %A M. G. Epitropakis %A V. P. Plagianakos %A M. N. Vrahatis %K differential evolution algorithm %K evolutionary computation %K optimization %K search problems %K self-balancing hybrid mutation operator %X The hybridization and composition of different Evolutionary Algorithms to improve the quality of the solutions and to accelerate execution is a common research practice. In this paper we propose a hybrid approach that combines differential evolution mutation operators in an attempt to balance their exploration and exploitation capabilities. Additionally, a self-balancing hybrid mutation operator is presented, which favors the exploration of the search space during the first phase of the optimization, while later opts for the exploitation to aid convergence to the optimum. Extensive experimental results indicate that the proposed approaches effectively enhance DEpsilas ability to accurately locate solutions in the search space. %B IEEE Congress on Evolutionary Computation, 2008. CEC 2008. (IEEE World Congress on Computational Intelligence) %C Hong Kong %8 June %G eng %R 10.1109/CEC.2008.4631159