T his 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 experim ental results of the proposed algorithm based on a mechanical design problem show promising result.

genetic algorithm, optimization, search