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Hybrid Modeling

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by J. N. Hooker
Citations:2 - 2 self
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BibTeX

@MISC{Hooker_hybridmodeling,
    author = {J. N. Hooker},
    title = {Hybrid Modeling},
    year = {}
}

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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.

Keyphrases

hybrid modeling    mixed integer linear programming    solution method    practical guideline    computational benefit    constraint programming    modeling practice    integrated framework    full computational resource    operation research    integrated modeling framework    artificial intelligence   

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