Sensitivity analysis of Parallel Cell Coordinate System in Many-objective Particle Swarm Optimization

Parallel Cell Coordinate System (PCCS) was proposed to evaluate the individual fitness in an archive and access the population progress in the evolutionary environment. In a Many-objective Optimization Problem (MaOP), it is much harder to tradeoff the convergence and diversity than in a Multiobjective Optimization Problem. To more effectively tackle the MaOPs, the PCCS and the aggregation-based approach are integrated into a Many-objective Optimization Particle Swarm Optimization (MaOPSO). In this paper, the sensitivity of PCCS is examined with respect to the number of objectives and the maximum size of an archive. The experimental results indicate that the MaOPSO performs better than MOEA/D in terms of IGD and HV metrics on the WFG test suit, and PCCS is not sensitive to the number of objectives and the maximum size of an archive.