Multi-objective evolutionary search performance with explicit building-block sizes for NPC problems

This research uses an explicit building block based MOEA to solve the multiobjective quadratic assignment problem. We use the multiobjective messy genetic algorithm II (MOMGA-II) to determine what role certain building blocks sizes play in filling up the Pareto front. Additionally, we investigate the role of the competitive template. The algorithm uses the competitive template by propagating it through all the building block sizes and by randomizing it for each building block size. We show that randomized competitive templates produce better results due to more exploration, and larger building block sizes are more common on the outer edges of the Pareto front because they fill more chromosome characteristics in the genotype space.