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Particle Swarm Optimization Based Global Descent Method
Author(s) -
Qian Chen,
Yasuda Keiichiro
Publication year - 2009
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20472
Subject(s) - metaheuristic , particle swarm optimization , descent (aeronautics) , benchmark (surveying) , mathematical optimization , multi swarm optimization , global optimization , computer science , gradient descent , descent direction , point (geometry) , derivative free optimization , swarm intelligence , algorithm , mathematics , artificial intelligence , engineering , artificial neural network , geography , geometry , geodesy , aerospace engineering
This letter proposes a new global descent method based on not only the concept of a conventional descent method in mathematical programming but also the concept of search direction in particle swarm optimization (PSO) in metaheuristics. The proposed method, called particle swarm optimization based global descent method (PSOGDM), consists of two main procedures; (i) determination of search direction and (ii) global optimization for given search direction. Although the search direction that has three parameters is decided based on the concept of PSO, the proposed PSOGDM is a single‐point search different from PSO. Global optimization for a given search direction is performed by PSO. The search capability of the proposed PSOGDM is examined based on the results of numerical experiments using five typical benchmark problems. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.