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Hybrid Modeling

In: Hybrid Optimization

Author

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  • John N. Hooker

    (Carnegie Mellon University)

Abstract

The modeling practices of constraint programming (CP), artificial intelligence, and operations research must be reconciled and integrated if the computational benefits of combining their solution methods are to be realized in practice. This chapter focuses on CP and mixed integer/linear programming (MILP), in which modeling systems are most highly developed. It presents practical guidelines and supporting theory for the two types of modeling. It then suggests how an integrated modeling framework can be designed that retains, and even enhances, the modeling power of CP while allowing the full computational resources of both fields to be applied and combined. A series of examples are used to compare modeling practices in CP, MILP, and an integrated framework.

Suggested Citation

  • John N. Hooker, 2011. "Hybrid Modeling," Springer Optimization and Its Applications, in: Pascal van Hentenryck & Michela Milano (ed.), Hybrid Optimization, edition 1, pages 11-62, Springer.
    • Handle: RePEc:spr:spochp:978-1-4419-1644-0_2
    DOI: 10.1007/978-1-4419-1644-0_2
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