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A pre-assignment heuristic algorithm for the Master Surgical Schedule Problem (MSSP)

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Abstract

In this paper a 0–1 linear programming model and a solution heuristic algorithm are developed in order to solve the so-called Master Surgical Schedule Problem (MSSP). Given a hospital department made up of different surgical units (i.e. wards) sharing a given number of Operating Rooms (ORs), the problem herein addressed is determining the assignment among wards and ORs during a given planning horizon, together with the subset of patients to be operated on during each day. Different resource constraints related to operating block time length, maximum OR overtime allowable by collective labour agreement and legislation, patient length of stay (LOS), available OR equipment, number of surgeons, number of stay and ICU beds, are considered. Firstly, a 0–1 linear programming model intended to minimise a cost function based upon a priority score, that takes into proper account both the waiting time and the urgency status of each patient, is developed. Successively, an heuristic algorithm that enables us to embody some pre-assignment rules to solve this NP-hard combinatorial optimisation problem, is presented. In particular, we force the assignment of each patient to a subset of days depending on his/her expected length of stay in order to allow closing some stay areas during the weekend and hence reducing overall hospitalisation cost of the department. The results of an extensive computational experimentation aimed at showing the algorithm efficiency in terms of computational time and solution effectiveness are given and analysed.

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Authors and Affiliations

  1. Department of Economics and Quantitative Methods (DIEM), University of Genova, Via Vivaldi 5, 16126, Genova, Italy

    Elena Tànfani & Angela Testi

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  1. Elena Tànfani
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  2. Angela Testi
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Correspondence to Elena Tànfani.

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Tànfani, E., Testi, A. A pre-assignment heuristic algorithm for the Master Surgical Schedule Problem (MSSP). Ann Oper Res 178, 105–119 (2010). https://doi.org/10.1007/s10479-009-0568-6

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  • DOI: https://doi.org/10.1007/s10479-009-0568-6

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