Chva´tal closures for mixed integer programming problems
Mathematical Programming: Series A and B
A hierarchy of relaxation between the continuous and convex hull representations
SIAM Journal on Discrete Mathematics
A lift-and-project cutting plane algorithm for mixed 0-1 programs
Mathematical Programming: Series A and B
Discrete Applied Mathematics
Generating Cuts from Multiple-Term Disjunctions
Proceedings of the 8th International IPCO Conference on Integer Programming and Combinatorial Optimization
On the Value of Binary Expansions for General Mixed-Integer Linear Programs
Operations Research
Valid inequalities for mixed integer linear programs
Mathematical Programming: Series A and B
Inequalities from Two Rows of a Simplex Tableau
IPCO '07 Proceedings of the 12th international conference on Integer Programming and Combinatorial Optimization
An algorithmic framework for convex mixed integer nonlinear programs
Discrete Optimization
Cook, Kannan and Schrijver's example revisited
Discrete Optimization
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In this paper, we give a finite disjunctive programming procedure to obtain the convex hull of general mixed-integer linear programs (MILP) with bounded integer variables. We propose a finitely convergent convex hull tree algorithm that constructs a linear program that has the same optimal solution as the associated MILP. In addition, we combine the standard notion of sequential cutting planes with ideas underlying the convex hull tree algorithm to help guide the choice of disjunctions to use within a cutting plane method. This algorithm, which we refer to as the cutting plane tree algorithm, is shown to converge to an integral optimal solution in finitely many iterations. Finally, we illustrate the proposed algorithm on three well-known examples in the literature that require an infinite number of elementary or split disjunctions in a rudimentary cutting plane algorithm.