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Testing cut generators for mixed-integer linear programming

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Abstract

In this paper, a methodology for testing the accuracy and strength of cut generators for mixed-integer linear programming is presented. The procedure amounts to random diving towards a feasible solution, recording several kinds of failures. This allows for a ranking of the accuracy of the generators. Then, for generators deemed to have similar accuracy, statistical tests are performed to compare their relative strength. An application on eight Gomory cut generators and six Reduce-and-Split cut generators is given. The problem of constructing benchmark instances for which feasible solutions can be obtained is also addressed.

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Authors and Affiliations

  1. Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA, 15213, USA

    François Margot

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  1. François Margot
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Correspondence to François Margot.

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Supported by ONR grant N00014-09-1-0033.

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Margot, F. Testing cut generators for mixed-integer linear programming. Math. Prog. Comp. 1, 69–95 (2009). https://doi.org/10.1007/s12532-009-0003-7

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  • DOI: https://doi.org/10.1007/s12532-009-0003-7

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