Hybrid Artificial Glowworm Swarm Optimization Algorithm for Solving Constrained Engineering Problem

Qi Fang Luo; Jun Li Zhang

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

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210Hybrid Artificial Glowworm Swarm Optimization...

Hybrid Artificial Glowworm Swarm Optimization Algorithm for Solving Constrained Engineering Problem

Abstract:

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.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

823-827

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.823

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Online since:

February 2011

Authors:

Qi Fang Luo, Jun Li Zhang

Keywords:

Engineering Optimization Design, Glowworm Swarm Optimization, Hybrid Optimization Algorithm

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