We study mixed integer nonlinear programs (MINLP)s that are driven by a collection of indicator variables where each indicator variable controls a subset of the decision variables. An indicator variable, when it is “turned off”, forces some of the decision variables to assume fixed values, and, when it is “turned on”, forces them to belong … Read more
This paper shows how valid inequalities based on the mixing set can be used in a mixed integer programming (MIP) solver. It discusses the relation of mixing inequalities to flow path and mixed integer rounding in- equalities and how currently used separation algorithms already generate cuts implicitly that can be seen as mixing cuts. Further … Read more
In this paper we study an exact separation algorithm for mixed knapsack sets with the aim of evaluating its effectiveness in a cutting plane algorithm for Mixed-Integer Programming. First proposed by Boyd in the 90’s, exact knapsack separation has recently found a renewed interest. In this paper we present a “lightweight” exact separation procedure for … Read more
We describe a rudimentary branch-and-cut algorithm for solving integer bilevel linear programs that extends existing techniques for standard integer linear programs to this very challenging computational setting. The algorithm improves on the branch-and-bound algorithm of Moore and Bard in that it uses cutting plane techniques to produce improved bounds, does not require specialized branching strategies, … Read more
In the Generalized Quadratic Assignment Problem (GQAP), given M facilities and N locations, one must assign each facility to one location so as to satisfy the given facility space requirements, minimizing the sum of installation and facility interaction costs. In this paper, we propose a new Lagrangean relaxation and a lower bounding procedure for the … Read more
As a traditional model in the operations research and management science domain, lot-sizing problem is embedded in many application problems such as production and inventory planning and has been consistently drawing attentions from researchers. There is significant research progress on polynomial time algorithm developments for deterministic uncapacitated lot-sizing problems based on Wagner-and-Whitin property. However, in … Read more
We develop sharp bounds on turnpike theorems for the unbounded knapsack problem. Turnpike theorems specify when it is optimal to load at least one unit of the best item (i.e., the one with the highest “bang-for-buck” ratio) and, thus can be used for problem preprocessing. The successive application of the turnpike theorems can drastically reduce … Read more
We consider the problem of optimizing a nonlinear objective function over a weighted independence system presented by a linear-optimization oracle. We provide a polynomial-time algorithm that determines an r-best solution for nonlinear functions of the total weight of an independent set, where r is a constant that depends on certain Frobenius numbers of the individual … Read more
We prove several inequalities on the determinants of sublattices in LLL-reduced bases. They generalize the fundamental inequalities of Lenstra, Lenstra, and Lovasz on the length of the shortest vector, and show that LLL-reduction finds not only a short vector, but also sublattices with small determinants. We also prove new inequalities on the product of the … Read more
Given a finite ground set N and a value vector a in R^N, we consider optimization problems involving maximization of a submodular set utility function of the form h(S)= f (sum_{i in S} a_i), S subseteq N, where f is a strictly concave, increasing, differentiable function. This function appears frequently in combinatorial optimization problems when … Read more