A polynomial case of cardinality constrained quadratic optimization problem

We investigate in this paper a fixed parameter polynomial algorithm for the cardinality constrained quadratic optimization problem, which is NP-hard in general. More specifically, we prove that, given a problem of size $n$, the number of decision variables, and $s$, the cardinality, if, for some $0

Some Results on the Strength of Relaxations of Multilinear Functions

We study approaches for obtaining convex relaxations of global optimization problems containing multilinear functions. Specifically, we compare the concave and convex envelopes of these functions with the relaxations that are obtained with a standard relaxation approach, due to McCormick. The standard approach reformulates the problem to contain only bilinear terms and then relaxes each term … Read more

On semidefinite programming relaxations of maximum k-section

We derive a new semidefinite programming bound for the maximum k-section problem. For k=2 (i.e. for maximum bisection), the new bound is least as strong as the well-known bound by Frieze and Jerrum [A. Frieze and M. Jerrum. Improved Approximation Algorithms for MAX k-CUT and MAX BISECTION. Algorithmica, 18(1): 67-81, 1997]. For k > 2 … Read more

A Faster Algorithm for Quasi-convex Integer Polynomial Optimization

We present a faster exponential-time algorithm for integer optimization over quasi-convex polynomials. We study the minimization of a quasi-convex polynomial subject to s quasi-convex polynomial constraints and integrality constraints for all variables. The new algorithm is an improvement upon the best known algorithm due to Heinz (Journal of Complexity, 2005). A lower time complexity is … Read more

Symmetry-exploiting cuts for a class of mixed-0/1 second order cone programs

We will analyze mixed 0/1 second order cone programs where the fractional and binary variables are solely coupled via the conic constraints. For this special type of mixed-integer second order cone programs we devise a cutting-plane framework based on the generalized Benders cut and an implicit Sherali-Adams reformulation. We show that the resulting cuts are … Read more

Explicit Convex and Concave Envelopes through Polyhedral Subdivisions

In this paper, we derive explicit characterizations of convex and concave envelopes of several nonlinear functions over various subsets of a hyper-rectangle. These envelopes are obtained by identifying polyhedral subdivisions of the hyper-rectangle over which the envelopes can be constructed easily. In particular, we use these techniques to derive, in closed-form, the concave envelopes of … Read more

On Maximal S-free Convex Sets

Let S be a subset of integer points that satisfy the property that $conv(S) \cap Z^n = S$. Then a convex set K is called an S-free convex set if $int(K) \cap S = \emptyset$. A maximal S-free convex set is an S-free convex set that is not properly contained in any S-free convex set. … Read more

Solving the quadratic assignment problem by means of general purpose mixed integer linear programming solvers

The Quadratic Assignment Problem (QAP) can be solved by linearization, where one formulates the QAP as a mixed integer linear programming (MILP) problem. On the one hand, most of these linearization are tight, but hardly exploited within a reasonable computing time because of their size. On the other hand, Kaufman and Broeckx formulation [1] is … Read more

On mixed integer reformulations of monotonic probabilistic programming problems with discrete distributions

The paper studies large scale mixed integer reformulation approach to stochastic programming problems containing probability and quantile functions, under assumption of discreteness of the probability distribution involved. Jointly with general sample approximation technique and contemporary mixed integer programming solvers the approach gives a regular framework to solution of practical probabilistic programming problems. In the literature … Read more