The ant colony optimization algorithm for multiobjective optimization non-compensation model problem staff selection

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Abstract

This paper describes proposal for the application to modify the Ant Colony Optimization for multiobjective optimization non-compensation model problem staff selection. After analyzing the combinatorial problem involving multicriterial process of recruitment and selection model, it proposed non-compensating its solution using the modified ACO heuristic strategy. This shows that the lack of opportunities to receive appropriate the resulting matrix is related to the accurate prediction of the decision at an acceptable as satisfactory for implementation only available deterministic algorithms. © 2010 Springer-Verlag Berlin Heidelberg.

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Tadeusiewicz, R., & Lewicki, A. (2010). The ant colony optimization algorithm for multiobjective optimization non-compensation model problem staff selection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6382 LNCS, pp. 44–53). https://doi.org/10.1007/978-3-642-16493-4_5

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