Title :
Ensemble crowding differential evolution with neighborhood mutation for multimodal optimization
Author :
Hui, S. Y. Ron ; Suganthan, P.
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
Abstract :
Many optimization problems possess multiple global solutions or comparably fit local solutions. These multimodal optimization problems require the identification of not just one global optimal, but also multiple compatible solutions. Differential Evolution (DE) has been demonstrated to be highly effective for solving single-objective unimodal problems, but its loss of diversity over the course of evolution prevents it from locating multiple compatible solutions. Our proposed method combines the diversity maintenance of niching and neighborhood mutation techniques with the versatility of ensemble parameters for DE to enhance the exploitation of individual peaks on difficult multi-modal problems. Greedy local mutation strategy and crossover are shown to have improved the performance of the neighborhood crowding DE (NCDE) in our experiment with 14 common multimodal benchmark functions.
Keywords :
evolutionary computation; greedy algorithms; NCDE; crossover; diversity maintenance; ensemble crowding differential evolution; greedy local mutation strategy; multimodal benchmark function; multimodal optimization; multimodal problem; neighborhood crowding DE; neighborhood mutation technique; niching technique; single-objective unimodal problem; Convergence; Evolution (biology); Maintenance engineering; Optimization; Sociology; Statistics; Vectors; Differential Evolution (DE); Multimodal optimization; ensemble parameters; neighborhood mutation; niching;
Conference_Titel :
Differential Evolution (SDE), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/SDE.2013.6601453