DocumentCode :
722440
Title :
Robust differential evolution for solving numerical optimization problems
Author :
Chun-Ling Lin ; Sheng-Ta Hsieh ; Huang-Lyu Wu ; Tse Su
Author_Institution :
Dept. of Electr. Eng., Ming Chi Univ. of Technol. New Taipei City, Taipei, Taiwan
fYear :
2015
fDate :
2-4 March 2015
Firstpage :
122
Lastpage :
125
Abstract :
In this paper, the robust mutation strategy for differential evolution (DE) is proposed for Enhancing its solution searching abilities. Also, the elitist crossover is involved to produce potential vectors. In the experiments, fifteen CEC 2005 test functions, which include uni-modal and multi-modal functions, are adopted for testing the proposed method and compare its performance with three DE variants. From the results, it can be observed that the proposed method performs better than other DE approaches on most test functions.
Keywords :
evolutionary computation; optimisation; search problems; vectors; DE; differential evolution; elitist crossover; numerical optimization problem; robust mutation strategy; searching ability; vector; Radio access networks; differential evolution; elitist crossover; optimization; robust mutation; vector;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Networks and Intelligent Systems (INISCom), 2015 1st International Conference on
Conference_Location :
Tokyo
Type :
conf
DOI :
10.4108/icst.iniscom.2015.258331
Filename :
7157832
Link To Document :
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