Hybrid Modeling.pdf.pdf' (395.87 kB)
journal contributionposted on 2007-05-01, 00:00 authored by John N. Hooker
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), inwhich 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.