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Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Efficient selection operators in NSGA-II for Solving Bi-Objective Multi-Skill Resource-Constrained Project Scheduling Problem

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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 8386 ()

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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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