Agent-based multi-objective evolutionary algorithm with sexual selection

Evolutionary algorithms are (meta-)heuristic techniques used in the case of search, optimization, and adaptation problems, which cannot be solved with the use of traditional methods. Sexual selection mechanism helps to maintain the population diversity in evolutionary algorithms. In this paper the agent-based realization of multi-objective evolutionary algorithm with sexual selection mechanism is presented. The system is evaluated with the use of Zitzler's test problems and compared to "classical" multi-objective evolutionary algorithms.