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Grammar-Based Integer Programming Models for Multiactivity Shift Scheduling

  • Marie-Claude Côté

    ()

    (CIRRELT and Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, Montréal, Québec H3C 3A7, Canada)

  • Bernard Gendron

    ()

    (CIRRELT and Département d'Informatique et de Recherche Opérationnelle, Université de Montréal, Montréal, Québec H3C 3J7, Canada)

  • Louis-Martin Rousseau

    ()

    (CIRRELT and Département de Mathématiques et de Génie Industriel, École Polytechnique de Montréal, Montréal, Québec H3C 3A7, Canada)

Registered author(s):

    This paper presents a new implicit formulation for shift scheduling problems, using context-free grammars to model the rules for the composition of shifts. From the grammar, we generate an integer programming (IP) model having a linear programming relaxation equivalent to that of the classical set covering model. When solved by a state-of-the-art IP solver on problem instances with a small number of shifts, our model, the set covering formulation, and a typical implicit model from the literature yield comparable solution times. On instances with a large number of shifts, our formulation shows superior performance and can model a wider variety of constraints. In particular, multiactivity cases, which cannot be modeled by existing implicit formulations, can easily be handled with grammars. We present comparative experimental results on a large set of instances involving one work activity, as well as on problems dealing with up to 10 work activities. This paper was accepted by Dimitris Bertsimas, optimization.

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    File URL: http://dx.doi.org/10.1287/mnsc.1100.1264
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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 57 (2011)
    Issue (Month): 1 (January)
    Pages: 151-163

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    Handle: RePEc:inm:ormnsc:v:57:y:2011:i:1:p:151-163
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