Variable-based ε — PAES with adaptive fertility rate

This paper suggests a new multi-objective evolutionary algorithm. The proposed ε-PAES combines ideas from two well-known algorithms, namely PAES and ε-MOEA. The adopted ideas are accompanied with a front-based adaptive fertility-rate and a variable-based approach. The algorithm performs the optimization process using separated local searches per each one of the problem´s decision variables, by adaptation of the associated step sizes. The performance of the algorithm is checked on several test cases and is statistically compared with the performance of ε-MOEA. It is found that the proposed algorithm achieves results of similar quality to ε-MOEA while consuming less computational resources.