Paper Info
Title
Adaptive Grouping Brain Storm Optimization for Multimodal Optimization Problems
Abstract
Multimodal optimization problem exists in multiple global and many local optimal solutions. The difficulty of solving these problems is finding as many local optimal peaks as possible on the premise of ensuring global optimal precision. This article presents adaptive grouping brainstorm optimization (AGBSO) for solving these problems. In this article, adaptive grouping strategy is proposed for achieving adaptive grouping without providing any prior knowledge by users. For enhancing the diversity and accuracy of the optimal algorithm, elite reservation strategy is proposed to put central particles into an elite pool, and peak detection strategy is proposed to delete particles far from optimal peaks in the elite pool. Finally, this article uses testing functions with different dimensions to compare the convergence, accuracy, and diversity of AGBSO with BSO. Experiments verify that AGBSO has great localization ability for local optimal solutions while ensuring the accuracy of the global optimal solutions.
Year
DOI
Venue
2021
10.4018/IJSIR.2021100105
INTERNATIONAL JOURNAL OF SWARM INTELLIGENCE RESEARCH
Keywords
DocType
Volume
Adaptive Grouping, Brain Storm Optimization, Elite Reservation, Multimodal Optimization, Peak Detection, Space Size Approximation
Journal
12
Issue
ISSN
Citations 
4
1947-9263
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Yao Peng100.68
Zepeng Shen200.68
Shiqi Wang300.68