Given $A\in Z^{m\times n}$ and $b\in Z^m$, we consider the integer program $\max \{c’x\vert Ax=b;x\in N^n\}$ and provide an equivalent and explicit linear program $\max \{\widehat{c}’q\vert M q=r;q\geq 0\}$, where $M,r,\widehat{c}$ are easily obtained from $A,b,c$ with no calculation. We also provide an explicit algebraic characterization of the integer hull of the convex polytope $P=\{x\in\R^n\vert … Read more
Given a convex rational polytope $\Omega(b):=\{x\in\R^n_+\,|\,Ax=b\}$, we consider the function $b\mapsto f(b)$, which counts the nonnegative integral points of $\Omega(b)$. A closed form expression of its $\Z$-transform $z\mapsto \mathcal{F}(z)$ is easily obtained so that $f(b)$ can be computed as the inverse $\Z$-transform of $\mathcal{F}$. We then provide two variants of an inversion algorithm. As a … Read more
The lot-sizing polytope is a fundamental structure contained in many practical production planning problems. Here we study this polytope and identify facet-defining inequalities that cut off all fractional extreme points of its linear programming relaxation, as well as liftings from those facets. We give a polynomial-time combinatorial separation algorithm for the inequalities when capacities are … Read more
We study the mixed-integer knapsack polyhedron, that is, the convex hull of the mixed-integer set defined by an arbitrary linear inequality and the bounds on the variables. We describe facet-defining inequalities of this polyhedron that can be obtained through sequential lifting of inequalities containing a single integer variable. These inequalities strengthen and/or generalize known inequalities … Read more
Column generation has become a powerful tool in solving large scale integer programs. We argue that most of the often reported compatibility issues between pricing oracle and branching rules disappear when branching decisions are based on the reduction of the variables of the oracle’s domain. This can be generalized to branching on variables of a … Read more
We develop a simple and yet very efficient exact algorithm for the problem of locating $p$ facilities and assigning clients to them in order to minimize the maximum distance between a client and the facility to which it is assigned. The algorithm iteratively sets a maximum distance value within which it tries to assign all … Read more
Based on the recent approach of Bertsimas and Sim \cite{bs1, bs2} to robust optimization in the presence of data uncertainty, we prove a bound on the probability that the robust solution gives an objective function value worse than the robust objective function value, under the assumption that only cost coefficients are subject to uncertainty. A … Read more
We study the lift-and-project procedures for solving combinatorial optimization problems, as described by Lov\’asz and Schrijver, in the context of the stable set problem on graphs. We investigate how the procedures’ performances change as we apply fundamental graph operations. We show that the odd subdivision of an edge and the subdivision of a star operations … Read more
We survey how semidefinite programming can be used for finding good approximative solutions to hard combinatorial optimization problems. Citation Preliminary version appeared as Report PNA-R0210, CWI, Amsterdam, April 2002. To appear as Chapter in the Handbook on Discrete Optimization, K. Aardal, G. Nemhauser, R. Weismantel, eds., Elsevier Publishers. Article Download View Semidefinite programming and integer … Read more
Dantzig-Wolfe decomposition and column generation, devised for linear programs, is a success story in large scale integer programming. We outline and relate the approaches, and survey mainly recent contributions, not found in textbooks, yet. We emphasize on the growing understanding of the dual point of view, which brought considerable progress to the column generation theory … Read more