Hybrid Artificial Glowworm Swarm Optimization Algorithm for Solving Constrained Engineering Problem

被引：3

作者：

Luo, Qifang ^{[1
]}

Zhang, Junli ^{[1
]}

机构：

[1] Guangxi Univ Nationalities, Coll Math & Comp Sci, Nanning 530006, Guangxi, Peoples R China

来源：

ADVANCED RESEARCH ON INDUSTRY, INFORMATION SYSTEMS AND MATERIAL ENGINEERING, PTS 1-7 | 2011年 / 204-210卷

关键词：

Glowworm swarm optimization; hybrid optimization algorithm; engineering optimization design;

D O I：

10.4028/www.scientific.net/AMR.204-210.823

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, based on glowworm swarm (GS) and artificial fish swarm (AFS) with differential evolution (DE) optimization algorithm, a new hybrid artificial glowworm swarm optimization (HGSO) algorithm is proposed. We use HGSO to solve engineering optimization design problem. The results show that the HGSO has faster convergence, higher precision and is more effective for solving constrained engineering optimization problem.

引用

页码：823 / 827

页数：5

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