With stochastic integer programming as the motivating application, we investigate techniques to use integrality constraints to obtain improved cuts within a Benders decomposition algorithm. We compare the effect of using cuts in two ways: (i) cut-and-project, where integrality constraints are used to derive cuts in the extended variable space, and Benders cuts are then used … Read more
We schedule appointments with random service durations on multiple servers with operating time limits. We minimize the costs of operating servers and serving appointments, subject to a joint chance constraint limiting the risk of server overtime. Using finite samples of the uncertainty, we formulate the problem as a mixed-integer linear program, and propose a two-stage … Read more
Many important NP-hard combinatorial problems can be efficiently approximated using semidefinite programming relaxations. We propose a new hierarchy of semidefinite relaxations for classes of such problems that based on graphs and for which the projection of the problem onto a subgraph shares the same structure as the original problem. This includes the well-studied max-cut and … Read more
We propose the bound-optimal cutting plane method. It is a new paradigm for cutting plane generation in Mixed Integer Programming allowing for the simultaneous generation of k cuts which, when added to the current Linear Programming elaxation, yield the largest bound improvement. By Linear Programming duality arguments and standard linearization techniques we show that, for … Read more
Routing problems stand among the hardest combinatorial problems to find high quality bounds or to prove new optimal solutions. In this thesis, we tackle the Capacitated Arc Routing Problem (CARP) and the Generalized Vehicle Routing Problem (GVRP). For both problems, there are a set of customers spread over a given graph, where each customer has … Read more
In this paper branching for attacking MILP is investigated. Under certain circumstances branches can be done concurrently. By introducing a new calculus it is shown there are restrictions for dual values. As a second result of this study a new class of cuts for MILP is found, which are defined by those values. This class … Read more
We investigate the computational potential of split inequalities for non-convex quadratic integer programming, first introduced by Letchford and further examined by Burer and Letchford. These inequalities can be separated by solving convex quadratic integer minimization problems. For small instances with box-constraints, we show that the resulting dual bounds are very tight; they can close a … Read more
We study approaches for the exact solution of the \NP–hard minimum spanning tree problem under conflict constraints. Given a graph $G(V,E)$ and a set $C \subset E \times E$ of conflicting edge pairs, the problem consists of finding a conflict-free minimum spanning tree, i.e. feasible solutions are allowed to include at most one of the … Read more
Motivated by mixed-integer, nonlinear optimization problems, we derive linear inequality characterizations for sets of the form conv{(x, q ) \in R^d × R : q \in Q(x), x \in R^d – int(P )} where Q is convex and differentiable and P \subset R^d . We show that in several cases our characterization leads to polynomial-time … Read more
Research on due date oriented objectives in the parallel machine environment is at best scarce compared to objectives such as minimizing the makespan or the completion time related performance measures. Moreover, almost all existing work in this area is focused on the identical parallel machine environment. In this study, we leverage on our previous work … Read more