|Table of Contents|

Novel Dynamic Population and Anisomerous Crossover Genetic Algorithm

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2007年04期
Page:
444-448
Research Field:
Publishing date:
2007-08-30

Info

Title:
Novel Dynamic Population and Anisomerous Crossover Genetic Algorithm
Author(s):
ZHANG Jin-ping12LIU Jie1LI Yun-gong1
1.School of Mechanical Engineering and Automation,Northeastern University,Shengyang 110004,China;2.Department of Mechanical Engineering,Shenyang Institute of Chemical Technology,Shenyang 110142,China
Keywords:
genet ic algo rithm real coding crossover opt im ization convergence
PACS:
TP18
DOI:
-
Abstract:
The shortcom ings and the essent ia ls o f genetic algorithm are discussed. A novel genetic a lgorithm is proposed whose popu lat ion is dynam ic and whose crossover is anisomerous. In every propagate process, the propagate tmi es of parents random fluctuates in lmi itat ive range, and the size of population is dynam ic. A ccord ing to the principle of balance nature, the size of population is kept at the average of w ave by the crossover and se lection. In order to mi prove the variety and universa lity of the new populat ion in the parameter space, themethod of anisomerous crossover is designed. Based on the new a lgorithm, the method of double select ion is presented. Calculating some typica l instants and comparingw ith other genetic algorithms, the results show that the convergence rate, success rate and ant-i premature of the nove l genetic algorthm are superior.

References:

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Last Update: 2007-08-30