IAMGA: intimate-based assortative mating genetic algorithm

Authors:
Fatemeh Ramezani;Shahriar Lotfi
Affiliations:
Computer Enginering Department, College of Nabi Akram, Iran;Computer Science Department, University of Tabriz, Iran
Venue:
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Year:
2011

Citing 7
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Abstract

Standard Genetic Algorithms (SGAs) is modeled as a simple set of fixed size individuals and each individual has no gender. The idea is based on non-random mating and important role of religious in the organization of societies. Essential concepts of religions are commandments and religious customs, which influence the behavior of the individuals. This paper proposes the Intimate-Based Assortative Mating Genetic Algorithm (IAMGA) and explores the affect of including intimate-based assortative mating to improve the performance of genetic algorithms. The IAMGA combined gender-based, variable-size and intimate-based assortative mating feature. All mentioned benchmark instances were clearly better than the performance of a SGA.