Lower bounds for Chvátal-Gomory style operators

Valid inequalities or cutting planes for (mixed-) integer programming problems are an essential theoretical tool for studying combinatorial properties of polyhedra. They are also of utmost importance for solving optimization problems in practice; in fact any modern solver relies on several families of cutting planes. The Chvátal-Gomory procedure, one such approach, has a peculiarity that … Read more

Strong Branching Inequalities for Convex Mixed Integer Nonlinear Programs

Strong branching is an effective branching technique that can significantly reduce the size of the branch-and-bound tree for solving Mixed Integer Nonlinear Programming (MINLP) problems. The focus of this paper is to demonstrate how to effectively use discarded information from strong branching to strengthen relaxations of MINLP problems. Valid inequalities such as branching-based linearizations, various … Read more

Cuts over Extended Formulations by Flow Discretization

Large-sized extended formulations have the potential for providing high-quality bounds on some combinatorial optimization problems where the natural formulations perform poorly. This chapter discusses the use of some families of cuts that have been recently applied on extended formulations that are obtained by the discretization of the continuous variables occurring in the natural formulation of … Read more

Sell or Hold: a simple two-stage stochastic combinatorial optimization problem

There are $n$ individual assets and $k$ of them are to be sold over two stages. The first-stage prices are known and the second-stage prices have a known distribution. The sell or hold problem (SHP) is to determine which assets are to be sold at each stage to maximize the total expected revenue. We show … Read more

Probabilistic Set Covering with Correlations

We consider a probabilistic set covering problem where there is uncertainty regarding whether a selected set can cover an item, and the objective is to determine a minimum-cost combination of sets so that each item is covered with a pre-specified probability. To date, literature on this problem has focused on the special case in which … Read more

Algorithimic and Complexity Results for Cutting Planes Derived from Maximal Lattice-Free Convex Sets

We study a mixed integer linear program with $m$ integer variables and $k$ non-negative continuous variables in the form of the relaxation of the corner polyhedron that was introduced by Andersen, Louveaux, Weismantel and Wolsey [\emph{Inequalities from two rows of a simplex tableau}, Proc.\ IPCO 2007, LNCS, vol.~4513, Springer, pp.~1–15]. We describe the facets of … Read more

Complexity results for the gap inequalities for the max-cut problem

In 1996, Laurent and Poljak introduced an extremely general class of cutting planes for the max-cut problem, called gap inequalities. We prove several results about them, including the following: (i) there must exist non-dominated gap inequalities with gap larger than 1, unless NP = co-NP; (ii) there must exist non-dominated gap inequalities with exponentially large … Read more

On the generation of symmetry breaking constraints for mathematical programs

Mathematical programs whose formulation is symmetric often take a long time to solve using Branch-and-Bound type algorithms, because of the several symmetric optima. One of the techniques used to decrease the adverse effects of symmetry is adjoining symmetry breaking constraints to the formulation before solving the problem. These constraints aim to make some of the … Read more

Strong Dual for Conic Mixed-Integer Programs

Mixed-integer conic programming is a generalization of mixed-integer linear programming. In this paper, we present an extension of the duality theory for mixed-integer linear programming to the case of mixed-integer conic programming. In particular, we construct a subadditive dual for mixed-integer conic programming problems. Under a simple condition on the primal problem, we are able … Read more

Column Generation for Extended Formulations

Working in an extended variable space allows one to develop tight reformulations for mixed integer programs. However, the size of the extended formulation grows rapidly too large for a direct treatment by a MIP-solver. Then, one can use projection tools and derive valid inequalities for the original formulation, or consider an approximate extended formulation (f.i., … Read more