Efficient selection operators in NSGA-II for solving bi-objective multi-skill resource-constrained project scheduling problem

Abstract

This paper presents multiple variances of selection operator used in Non-dominated Sorting Genetic Algorithm II applied to solving Bi-Objective Multi-Skill Resource Constrained Project Scheduling Problem. A hybrid Differential Evolution with Greedy Algorithm has been proven to work very well on the researched problem and so it is used to probe the multi-objective solution space. It is then determined whether a multi-objective approach can outperform single-objective approaches in finding potential Pareto Fronts. Additional modified selection operators and a clone prevention method have been introduced and experiments have shown the increase in efficiency caused by their utilization.