Improved differential evolution based on multi-armed bandit for multimodal optimization problems

2021 ◽  
Author(s):  
Suchitra Agrawal ◽  
Aruna Tiwari ◽  
Prathamesh Naik ◽  
Arjun Srivastava
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Multimodal Optimization

scholarly journals A Multi-Angle Hierarchical Differential Evolution Approach for Multimodal Optimization Problems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 178322-178335
Author(s):  
Zhao Hong ◽  
Zong-Gan Chen ◽  
Dong Liu ◽  
Zhi-Hui Zhan ◽  
Jun Zhang
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Multimodal Optimization ◽  
Evolution Approach

Hypercube-Based Crowding Differential Evolution with Neighborhood Mutation for Multimodal Optimization

2018 ◽  
Vol 9 (2) ◽  
pp. 15-27
Author(s):  
Haihuang Huang ◽  
Liwei Jiang ◽  
Xue Yu ◽  
Dongqing Xie
Keyword(s):  
Differential Evolution ◽  
Euclidean Distance ◽  
Optimization Problems ◽  
Random Search ◽  
Adaptive Method ◽  
Radius Vector ◽  
Multimodal Optimization ◽  
Optimal Solutions ◽  
Reasonable Range ◽  
Neighborhood Mutation

In reality, multiple optimal solutions are often necessary to provide alternative options in different occasions. Thus, multimodal optimization is important as well as challenging to find multiple optimal solutions of a given objective function simultaneously. For solving multimodal optimization problems, various differential evolution (DE) algorithms with niching and neighborhood strategies have been developed. In this article, a hypercube-based crowding DE with neighborhood mutation is proposed for such problems as well. It is characterized by the use of hypercube-based neighborhoods instead of Euclidean-distance-based neighborhoods or other simpler neighborhoods. Moreover, a self-adaptive method is additionally adopted to control the radius vector of a hypercube so as to guarantee the neighborhood size always in a reasonable range. In this way, the algorithm will perform a more accurate search in the sub-regions with dense individuals, but perform a random search in the sub-regions with only sparse individuals. Experiments are conducted in comparison with an outstanding DE with neighborhood mutation, namely NCDE. The results show that the proposed algorithm is promising and computationally inexpensive.

scholarly journals Automatic Niching Differential Evolution With Contour Prediction Approach for Multimodal Optimization Problems

2020 ◽  
Vol 24 (1) ◽  
pp. 114-128 ◽  
Author(s):  
Zi-Jia Wang ◽  
Zhi-Hui Zhan ◽  
Ying Lin ◽  
Wei-Jie Yu ◽  
Hua Wang ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Multimodal Optimization ◽  
Prediction Approach

scholarly journals Local Binary Pattern-Based Adaptive Differential Evolution for Multimodal Optimization Problems

2020 ◽  
Vol 50 (7) ◽  
pp. 3343-3357 ◽  
Author(s):  
Hong Zhao ◽  
Zhi-Hui Zhan ◽  
Ying Lin ◽  
Xiaofeng Chen ◽  
Xiao-Nan Luo ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Local Binary Pattern ◽  
Optimization Problems ◽  
Multimodal Optimization ◽  
Adaptive Differential Evolution
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