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PSO Driven Genetic Range Genetic Algorithms

[+] Author Affiliations
Masao Arakawa

Kagawa University, Kagawa, Japan

Paper No. DETC2005-84942, pp. 289-294; 6 pages
  • ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 31st Design Automation Conference, Parts A and B
  • Long Beach, California, USA, September 24–28, 2005
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4739-X | eISBN: 0-7918-3766-1
  • Copyright © 2005 by ASME


This paper deals with development of Genetic Range Genetic Algorithms (GRGAs). In GRGAs, one of the key is to set a new searching range, it needs to be followed after current searching situations, to be focused on local minute search and to be scattered as widely as possible for global search. However, first two strategies have a possibility of early stage convergence, and random scattering cause vain function calls to produce the range which seems no chance to prosper for a number of generations. In this paper, we propose a new method of setting it by using Particle Swarm Optimization (PSO) to overcome dilemma of the conventional method.

Copyright © 2005 by ASME



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