GADYM - A novel genetic algorithm in mechanical design problems

Khadiza Tahera, Raafat N. Ibrahim, Paul B. Lochert

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)

Abstract

This paper proposes a variant of genetic algorithm - GADYM, Genetic Algorithm with Gender-Age structure, DYnamic parameter tuning and Mandatory self perfection scheme. The motivation of this algorithm is to increase the diversity throughout the search procedure and to ease the difficulties associated with the tuning of GA parameters and operators. To promote diversity, GADYM combines the concept of gender and age in individuals of a traditional Genetic Algorithm and implements the self perfection scheme through sharing. To ease the parameter tuning process, the proposed algorithm uses dynamic environment in which heterogeneous crossover and selection techniques are used and parameters are updated based on deterministic rules. Thus, GADYM uses a combination of genetic operators and variable parameter values whereas a traditional GA uses fixed values of those. The experimental results of the proposed algorithm based on a mechanical design problem show promising result.

Original languageEnglish
Pages (from-to)2566-2581
Number of pages16
JournalJournal of Universal Computer Science
Volume14
Issue number15
Publication statusPublished - 1 Dec 2008

Keywords

  • Genetic algorithm
  • Optimization
  • Search

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