Competitive coevolution with K-Random Opponents for Pareto multiobjective optimization

In this paper, our objective is to conduct comprehensive tests for competitive coevolution using an evolutionary multiobjective algorithm for 3 dimensional problems. This competitive coevolution will. be implemented with K-Random Opponents strategy. A new algorithm which integrates Competitive Coevolution (CE) and the Strength Pareto Evolutionary Algorithm 2 (SPEA2) is proposed to achieve this objective. The resulting algorithm is referred to as the Strength Pareto Evolutionary Algorithm 2 with Competitive Coevolution (SPEA2-CE). The performance between SPEA2-CE is compared against SPEA2 to solve problems with each having three objectives using DTLZ suite of test problems. In general, the results show that the SPEA2-CE with K-Random Opponents performed well for the generational distance and coverage but performed less favorably for spacing.