An improved brainstorm optimization algorithm based on the strategy of random perturbation and vertical variation

被引：0

作者：

Bao, Gang ^{[1
]}

Li, Jie ^{[1
]}

Huang, Run-tao ^{[1
]}

Shen, Ke-xin ^{[1
]}

机构：

[1] China Three Gorges Univ, Hubei Key Lab Cascaded Hydropower Stn Operat & Co, Elect Engn & New Energy, Yichang 443002, Peoples R China

来源：

PROCEEDINGS OF THE 38TH CHINESE CONTROL CONFERENCE (CCC) | 2019年

关键词：

Brainstorm algorithm; Swarm intelligence; Random perturbation; Vertical variation; STORM OPTIMIZATION; GENETIC ALGORITHMS; DISPATCH;

D O I：

10.23919/chicc.2019.8865307

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The brainstorming optimization algorithm (BSO) is a swarm intelligence algorithm based on human creative thinking, which is inspired by the brainstorming process and proposed by Professor Yuhui Shi. It has been successfully applied to a lot of engineering problems involving optimization. In this paper, random perturbation strategy and vertical crossover variation are introduced to BSO to improve its performance. The specific idea is to increase the random disturbance and the vertical cross variation on the same variable when the individual is updated. The proposed algorithm Accelerating BSO (ABSO) is compared with BSO and other three algorithms(PSO, DE, CS) on 9 benchmark functions. From the results, both final solutions and convergence speed show the superiority of ABSO.

引用

页码：2046 / 2051

页数：6

共 21 条

[1] AN APPLICATION OF GENETIC ALGORITHMS FOR FLOW-SHOP PROBLEMS [J].