A networking requirement application by multi-objective genetic algorithms with Sexual Selection

This paper is aimed to present a genetic algorithm focusing on the sexual selection used the Pareto based approach for solving multi-objective optimization problems. It uses a concept of sexual selection with different types of gender and mutation rates based on the sex to produce offspring. Its performance was evaluated by the well-known benchmark functions as well as also tested with a networking requirement application, which is a multi-objective optimization problem. The proposed algorithm could successfully find solutions that meet user¿s requirements.