A study on synergy of multiple crossover operators in a hierarchical genetic algorithm applied to structural optimisation

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

Authors

antonio, cc (Author) FEUP

Journal

Title: Structural and Multidisciplinary Optimization

Vol. 38 No. 2

Pages: 117-135

ISSN: 1615-147X

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 18 Citations

Scopus - 28 Citations

Other information

Authenticus ID: P-003-MCJ

DOI: 10.1007/s00158-008-0268-x

Abstract (EN): Development of crossover operators is based on three different mechanisms: mating selection mechanism, offspring generation mechanism and offspring selection mechanism. Most crossover operators are able to get exploration or exploitation of the domain depending on the way they handle the current diversity of the population. Each crossover operator directs the search towards a different region in the neighbourhood of the parents. The quality of the elements belonging to the visited region depends on the particular problem to be solved. This is confirmed by the well known No Free Lunch (NFL) theorems. The simultaneous use of diverse crossover operators on the population may induce more efficient algorithms. The aim of this paper is to analyse and to study complementary properties resulting from synergy effects using several crossover operators in particular for a hierarchical genetic algorithm. The reached improvements using multiple crossover operators will be analysed through some standard optimisation examples of hybrid composite structures.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 19