Self-adaptation procedures in genetic algorithms applied to the optimal design of composite structures

• Type: Article in International Scientific Journal
• Date: 2009

Authors

antonio, cc (Author) FEUP

Journal

Title: International Journal of Mechanics and Materials in Design

Vol. 5

Pages: 289-302

ISSN: 1569-1713

Publisher: Springer Nature

Indexing

ISI Web of Knowledge

Scopus - 17 Citations

Scientific classification

FOS: Engineering and technology > Mechanical engineering

Other information

Authenticus ID: P-007-QNB

DOI: 10.1007/s10999-009-9102-x

Abstract (EN): It is recognized that the efficiency of Genetic Algorithms improves if some adaptive rules are included. In this work, adaptive properties in Genetic Algorithms applied to structural optimization are studied. The adaptive rules work by using additional information related to the behavior of state and design variables of the structural problem. At each generation, the self-adaptation of the genetic parameters to evolutionary conditions attempts to improve the efficiency of the genetic search. The introduction of adaptive rules occurs at three levels: (i) when defining the search domain in 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. © 2009 Springer Science+Business Media, B.V.

Language: English

Type (Professor's evaluation): Scientific