An effective explicit building block MOEA, the MOMGA-IIa

In the multiobjective messy genetic algorithm (MOMGA), the current version, MOMGA-IIa, incorporates efficient processes for obtaining the Pareto front while maintaining a distribution of solutions evaluating to vectors across the Pareto front. Initially described are principle classifiers within explicit building block (BB) multi-objective evolutionary algorithms (MOEAs). Novel design characteristics are addressed as essential elements for making MOMGA-IIa a state-of-the-art explicit BB MOEA. Additionally, a comparison of state-of-the-art explicit BB MOEAs using test suite problems, contemporary quality metrics, extensive testing, and statistical analysis is delivered. Finally, a supplementary historical view of the development of the MOMGA-series MOEA is provided