Self-adaptation in genetic algorithms applied to structural optimization

• Type: Article in International Conference Proceedings Book
• Date: 2008

Authors

Carlos Alberto Conceição António (Author) FEUP

Conference proceedings International

Title: EngOpt 2008 - International Conference on Engineering Optimization

Pages: 1-9

EngOpt 2008 - International Conference on Engineering Optimization

Rio de Janeiro, Brazil, June 1-5, 2008

Scientific classification

CORDIS: Technological sciences > Engineering

Other information

Authenticus ID: P-011-4JC

Abstract (EN): It is recognized that Genetic Algorithms efficiency improves clearly if some adaptive rules are included. In the present work, adaptive properties in Genetic Algorithms applied to structural optimization are studied. Here, adaptive rules perform using additional information related with the behavior of state and design variables of the structural problem. At each generation the selfadaptation of genetic parameters to evolutionary conditions aims to improve the efficiency of genetic search. The introduction of adaptive rules occurs at three levels: (i) when defining the search domain at each generation; (ii) considering a crossover operator based on commonality and local improvements; and (iii) by controlling mutation including behavioral data. Self-adaptation has proved to be highly beneficial in automatically and dynamically adjusting evolutionary parameters. Numerical examples showing these benefits are presented.

Language: English

Type (Professor's evaluation): Scientific

Notes: CD

No. of pages: 9