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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.