Attention-oriented Brain Storm Optimization for Multimodal Optimization Problems

Yang, Jian; Shi, Yuhui

10.1109/CEC45853.2021.9504871

2021

IEEE Congress on Evolutionary Computation (IEEE CEC)

978-1-7281-8394-7

2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021)

1968-1975

JUN 28-JUL 01, 2021

null,null,ELECTR NETWORK

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Population-based methods are often used to solve multimodal optimization problems. By combining niching or clustering strategy, the state-of-the-art approaches generally divide the population into several subpopulations to find multiple solutions for a problem at hand. However, these methods only guided by the fitness value during iterations, which are suffering from determining the number of subpopulations, i.e., the number of niche areas or clusters. To compensate for this drawback, this paper presents an Attention-oriented Brain Storm Optimization (ABSO) method that introduces the attention mechanism into a relatively new swarm intelligence algorithm, i.e., Brain Storm Optimization (BSO). By converting the objective space from the fitness space into "attention" space, the individuals are clustered and updated iteratively according to their salient values. Rather than converge to a single global optimum, the proposed method can guide the search procedure to converge to multiple "salient" solutions. The preliminary results show that the proposed method can locate multiple global and local optimal solutions of several multimodal benchmark functions. The proposed method needs less prior knowledge of the problem and can automatically converge to multiple optimums guided by the attention mechanism, which has excellent potential for further development.

Multimodal Optimization Brain Storm Optimization Attention Mechanism Population-based Algorithms

第一 ; 通讯

英语

CPCI-S ; EI

Science and Technology Innovation Committee Foundation of Shenzhen["JCYJ20200109141235597","ZDSYS201703031748284"]

Computer Science ; Engineering ; Mathematical & Computational Biology ; Operations Research & Management Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic ; Mathematical & Computational Biology ; Operations Research & Management Science

WOS:000703866100248

20220711650727

Evolutionary algorithms ; Iterative methods ; Optimization

Precipitation:443.3 ; Optimization Techniques:921.5 ; Numerical Methods:921.6

Web of Science

Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen, Peoples R China

Yang, Jian,Shi, Yuhui. Attention-oriented Brain Storm Optimization for Multimodal Optimization Problems[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2021:1968-1975.