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BDD-based heuristics for binary optimization

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Abstract

In this paper we introduce a new method for generating heuristic solutions to binary optimization problems. We develop a technique based on binary decision diagrams. We use these structures to provide an under-approximation to the set of feasible solutions. We show that the proposed algorithm delivers comparable solutions to a state-of-the-art general-purpose optimization solver on randomly generated set covering and set packing problems.

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Authors and Affiliations

  1. Tepper School of Business, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA, 15213, USA

    David Bergman, Andre A. Cire & Willem-Jan van Hoeve

  2. School of Business Administration, University of Miami, Coral Gables, FL, 33124-8237, USA

    Tallys Yunes

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  1. David Bergman
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  2. Andre A. Cire
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  3. Willem-Jan van Hoeve
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  4. Tallys Yunes
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Correspondence to Tallys Yunes.

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Bergman, D., Cire, A.A., van Hoeve, WJ. et al. BDD-based heuristics for binary optimization. J Heuristics 20, 211–234 (2014). https://doi.org/10.1007/s10732-014-9238-1

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  • DOI: https://doi.org/10.1007/s10732-014-9238-1

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