Abstract
We study the convex hull of the feasible set of the semi-continuous knapsack problem, in which the variables belong to the union of two intervals. Besides being important in its own right, the semi-continuous knapsack problem is a relaxation of general mixed-integer programming. We show how strong inequalities that are valid for the semi-continuous knapsack polyhedron can be derived and used as cuts in a branch-and-cut scheme for mixed-integer programming and problems with semi-continuous variables. We present computational results that demonstrate the effectiveness of these inequalities, which we call collectively semi-continuous cuts. Our computational experience also shows that dealing with semi-continuous constraints directly in the branch-and-cut algorithm through a specialized branching scheme and semi-continuous cuts is considerably more practical than the “textbook” approach of modeling semi-continuous constraints through the introduction of auxiliary binary variables in the model.
Partially supported by NSF grants DMI-0100020 and DMI-0121495. This paper is an extended abstract of [7].
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de Farias, I.R. (2004). Semi-continuous Cuts for Mixed-Integer Programming. In: Bienstock, D., Nemhauser, G. (eds) Integer Programming and Combinatorial Optimization. IPCO 2004. Lecture Notes in Computer Science, vol 3064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25960-2_13
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DOI: https://doi.org/10.1007/978-3-540-25960-2_13
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