BSO-CMA-ES: Brain Storm Optimization Based Covariance Matrix Adaptation Evolution Strategy for Multimodal Optimization

Qu，Liang; Zheng，Ruiqi; Shi，Yuhui

10.1007/978-981-16-7502-7_19

2021

1865-0929

1865-0937

Communications in Computer and Information Science

1454 CCIS

167-174

Recently, covariance matrix adaption evolution strategy (CMA-ES) and its variants have achieved great success in the continuous unimodal optimization tasks owing to its strong local search capabilities. However, it is precisely this capability that reduces the population diversity, which makes it unable to obtain the good performance on the multimodal optimization problems (MMOPs) aiming at locating all global optimal solutions during a single algorithm run. To address this problem, we first propose a swarm learning framework which is capable of collaboratively training multiple optimization algorithms (e.g., CMA-ES in this paper). Specifically, it introduces two objectives including individual objective and neighbor objective to balance the exploitation and exploration. The former guides each algorithm to locate at least one global optimal solution (exploitation), and the latter aims at maintaining the diversity of the different algorithms (exploration). Based on this framework, the brain storm optimization (BSO) is incorporated with multiple CMA-ES models, called BSO-CMA-ES, which makes the multiple CMA-ESs be collaboratively trained. To validate the effectiveness of the proposed method, several comparison algorithms are adopted and tested on typical MMOPs benchmark functions. Experimental results show that BSO-CMA-ES could obtain promising performance.

Brain storm optimization Covariance matrix adaptation evolution strategy Multimodal optimization Swarm learning

第一 ; 通讯

英语

EI

20214811220440

Evolutionary algorithms ; Optimal systems ; Optimization ; Storms ; Swarm intelligence

Precipitation:443.3 ; Artificial Intelligence:723.4 ; Mathematics:921 ; Optimization Techniques:921.5 ; Systems Science:961

2-s2.0-85119586817

Scopus

Department of Computer Science and Engineering,Southern University of Science and Technology,Guangdong,518055,China

Qu，Liang,Zheng，Ruiqi,Shi，Yuhui. BSO-CMA-ES: Brain Storm Optimization Based Covariance Matrix Adaptation Evolution Strategy for Multimodal Optimization[C],2021:167-174.