Efficient selection operators in NSGA-II for Solving Bi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem
Paweł B. Myszkowski, Maciej Laszczyk, Joanna Lichodij
DOI: http://dx.doi.org/10.15439/2017F317
Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 83–86 (2017)
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 is used as a baseline. This comparison is used to determine whether a multi-objective approach can outperform single-objective approaches in finding potential Pareto Fronts. Furthermore, found Pareto Fronts are compared using various measures. A modified selection operators have been introduced along with a clone prevention method. Experiments show the increase in efficiency caused by the use of new selection methods
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