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A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem
Department of Business Administration of Food and Agricultural Enterprises, University of Western Greece, G. Seferi 2, 30100, Agrinio, Greece
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Received: 6 March 2013; in revised form: 4 April 2013 / Accepted: 12 April 2013 / Published: 21 May 2013
Abstract: In this contribution, a generic two-phase stochastic variable neighborhood approach is applied to nurse rostering problems. The proposed algorithm is used for creating feasible and efficient nurse rosters for many different nurse rostering cases. In order to demonstrate the efficiency and generic applicability of the proposed approach, experiments with real-world input data coming from many different nurse rostering cases have been conducted. The nurse rostering instances used have significant differences in nature, structure, philosophy and the type of hard and soft constraints. Computational results show that the proposed algorithm performs better than six different existing approaches applied to the same nurse rostering input instances using the same evaluation criteria. In addition, in all cases, it manages to reach the best-known fitness achieved in the literature, and in one case, it manages to beat the best-known fitness achieved till now.
Keywords: nurse rostering; hospital personnel scheduling; stochastic variable neighborhood; two-phase algorithm; mutation element; swap selective mutation; reduce rosters’ cost
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Solos, I.P.; Tassopoulos, I.X.; Beligiannis, G.N. A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem. Algorithms 2013, 6, 278-308.
Solos IP, Tassopoulos IX, Beligiannis GN. A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem. Algorithms. 2013; 6(2):278-308.
Solos, Ioannis P.; Tassopoulos, Ioannis X.; Beligiannis, Grigorios N. 2013. "A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem." Algorithms 6, no. 2: 278-308.