Title :
A study on combination of differential evolution and evolution strategy
Author :
Yasuda, Keiichiro ; Makise, Kengo ; Tamura, Kenichi
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokyo Metropolitan Univ., Hachioji, Japan
Abstract :
In this paper, a new optimization method based on a combination of Differential Evolution (DE) and Evolution Strategy (ES), which belong to both Meta-Heuristics and Evolutionary Computation, are developed as a fast approximation optimization method. A weak point of DE is weak local search ability and considerable computation time for obtaining a good approximate solution. The proposed method aims at compensation for the weak points of DE by connecting ES with strong local search capacity. The effectiveness of the proposed method is confirmed through the numerical experiments.
Keywords :
approximation theory; evolutionary computation; search problems; approximation optimization method; differential evolution; evolution strategy; evolutionary computation; local search ability; meta-heuristics; Approximation methods; Gaussian distribution; Genetic algorithms; Optimization methods; Radiation detectors; Search problems; Vectors; Combination; Control Parameters; Differential Evolution; Evolution Strategy; Meta-Heuristics; Optimization;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6377789
