Open Access
Modified species-based differential evolution with self-adaptive radius for multi-modal optimization
B. Y. Qu,Ponnuthurai Nagaratnam Suganthan +1 more
- 01 Dec 2010
- pp 326-331
TL;DR: A modified SDE with a self-adaptive radius is proposed to overcome the difficulty of selecting the proper radius and improve the performance of SDE.
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Abstract: In real world optimization, many problems are not only target on finding one global peak, but also multiple global/local peaks. These problems are referred as multi-modal optimization problems. Various techniques that commonly known as niching are proposed to solve multi-modal problems. Species-based differential evolution (SDE) is one of the recent algorithms that use the notion of speciation for solving multimodal optimization problems. In this paper, a modified SDE with a self-adaptive radius is proposed to overcome the difficulty of selecting the proper radius and improve the performance of SDE. The proposed algorithms was tested on a set of classical benchmark multi-modal optimization problems and compared with the original SDE and several other niching algorithms in literature. As shown in the experimental results, the proposed algorithm outperforms these algorithms on the benchmark problems.
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Citations
Differential evolution based on fitness Euclidean-distance ratio for multimodal optimization
TL;DR: A modified Fitness Euclidean-distance Ratio technique is incorporated into differential evolution to enhance the DEs ability of locating and maintaining multiple peaks and the proposed simple algorithm performs better comparing with a number of state-of-the-art multimodal optimization approaches.
60
Fuzzy c-means clustering and partition entropy for species-best strategy and search mode selection in nonlinear optimization by differential evolution
Tetsuyuki Takahama,Setsuko Sakai +1 more
- 27 Jun 2011
TL;DR: This study proposes to utilize partition entropy given by fuzzy clustering for solving the degradation of differential Evolution and proposes to use a species-best strategy for improving the efficiency and the robustness of DE.
21
Differential Evolution Based on Fitness Euclidean-Distance Ratio for Multimodal Optimization
Jing Liang,Boyang Qu,Xiaobo Mao,Tie-Jun Chen +3 more
- 25 Jul 2012
TL;DR: Fitness euclidean-distance ratio (FER) is incorprated into differential evolution to solve multi-modal optimization problems and the proposed simple algorithm performs better comparing with a number of state-of-the-art multimodal optimization approaches.
12
•Dissertation
Evolutionary algorithms for solving multi-modal and multi-objective optimization problems
Boyang. Qu
- 01 Jan 2011
TL;DR: A summation of normalized objective values and diversified selection (SNOV-DS) method to replace the classical non-domination sorting and an ensemble of constraint handling methods (ECHM) to solve constrained multi-objective optimization problems, where each constraint handling method had its own population.
5
Differential Evolution with Graph-Based Speciation by Competitive Hebbian Rules
Tetsuyuki Takahama,Setsuko Sakai +1 more
- 25 Aug 2012
TL;DR: This study proposes a new speciation method "graph-based speciation" to keep the diversity of the search points and realize the global search, and utilizes the species-best strategy that can realize theglobal search using speciation and the local search around the seeds of species.
2
References
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