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An Efficient SMT Approach to Solve MRCPSP/max Instances with Tight Constraints on Resources

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Principles and Practice of Constraint Programming (CP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10416))

Abstract

The Multi-Mode Resource-Constrained Project Scheduling Problem with Minimum and Maximum Time Lags (MRCPSP/max) is a generalization of the well known Resource-Constrained Project Scheduling Problem. Recently, it has been shown that the benchmark datasets typically used in the literature can be easily solved by relaxing some resource constraints, which in many cases are dummy. In this work we propose new datasets with tighter resource limitations. We tackle them with an SMT encoding, where resource constraints are expressed as specialized pseudo-Boolean constraints and then translated into SAT. We provide empirical evidence that this approach is state-of-the-art for instances highly constrained by resources.

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Notes

  1. 1.

    This problem is denoted \(MPS|temp|C_{max}\) in [5] and \(m,1|gpr|C_{max}\) in [8]. It is also known as the Multi-mode RCPSP with Generalized Precedence Relations.

  2. 2.

    The solver used in the experiments, detailed results and the new instances are available at http://imae.udg.edu/recerca/LAP/.

References

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Acknowledgments

Work supported by grants TIN2015-66293-R (MINECO/ FEDER, UE), MPCUdG2016/055 (UdG), and Ayudas para Contratos Predoctorales 2016 (grant number BES-2016-076867, funded by MINECO and co-funded by FSE). We thank the authors of [12, 17] for sharing with us their solvers.

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Authors and Affiliations

  1. University of Girona, Girona, Spain

    Miquel Bofill, Jordi Coll, Josep Suy & Mateu Villaret

Authors
  1. Miquel Bofill
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  2. Jordi Coll
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  3. Josep Suy
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  4. Mateu Villaret
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Correspondence to Jordi Coll .

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  1. University of Toronto, Toronto, Ontario, Canada

    J. Christopher Beck

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Bofill, M., Coll, J., Suy, J., Villaret, M. (2017). An Efficient SMT Approach to Solve MRCPSP/max Instances with Tight Constraints on Resources. In: Beck, J. (eds) Principles and Practice of Constraint Programming. CP 2017. Lecture Notes in Computer Science(), vol 10416. Springer, Cham. https://doi.org/10.1007/978-3-319-66158-2_5

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  • DOI: https://doi.org/10.1007/978-3-319-66158-2_5

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