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Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139

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  • Juan Pablo Vielma

    (Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139)

Abstract

It is well known that selecting a good mixed-integer programming (MIP) formulation is crucial for effectively obtaining a solution with state-of-the art solvers. Although best practices and guidelines for constructing good formulations abound, there is rarely a single systematic construction approach that leads to the best possible formulation. Here, we introduce embedding formulations and complexity as a new MIP formulation paradigm for systematically constructing formulations for disjunctive constraints that are optimal with respect to size. More specifically, they yield the smallest possible ideal formulation (i.e., one whose LP relaxation has integral extreme points) among all formulations that only use 0-1 auxiliary variables. We use the paradigm to characterize optimal formulations for special ordered sets of type 2 and certain piecewise linear functions of two variables. We also show that the resultant formulations can provide a significant computational advantage over all known formulations for piecewise linear functions.

Suggested Citation

  • Juan Pablo Vielma, 2018. "Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139," Management Science, INFORMS, vol. 64(10), pages 4721-4734, October.
    • Handle: RePEc:inm:ormnsc:v:64:y:2018:i:10:p:4721-4734
    DOI: 10.287/mnsc.2017.2856
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    References listed on IDEAS

    as
    1. Toriello, Alejandro & Vielma, Juan Pablo, 2012. "Fitting piecewise linear continuous functions," European Journal of Operational Research, Elsevier, vol. 219(1), pages 86-95.
    2. Keely L. Croxton & Bernard Gendron & Thomas L. Magnanti, 2003. "A Comparison of Mixed-Integer Programming Models for Nonconvex Piecewise Linear Cost Minimization Problems," Management Science, INFORMS, vol. 49(9), pages 1268-1273, September.
    3. Juan Pablo Vielma & Shabbir Ahmed & George Nemhauser, 2010. "Mixed-Integer Models for Nonseparable Piecewise-Linear Optimization: Unifying Framework and Extensions," Operations Research, INFORMS, vol. 58(2), pages 303-315, April.
    4. Roberto Roberti & Enrico Bartolini & Aristide Mingozzi, 2015. "The Fixed Charge Transportation Problem: An Exact Algorithm Based on a New Integer Programming Formulation," Management Science, INFORMS, vol. 61(6), pages 1275-1291, June.
    5. Alan S. Manne, 1960. "On the Job-Shop Scheduling Problem," Operations Research, INFORMS, vol. 8(2), pages 219-223, April.
    6. Miles Lubin & Iain Dunning, 2015. "Computing in Operations Research Using Julia," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 238-248, May.
    7. LEE, Jon & WILSON, Dan, 2001. "Polyhedral methods for piecewise-linear functions I: the lambda method," LIDAM Reprints CORE 1493, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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