We present a mixed-integer nonlinear optimization model for computing the optimal expansion of an existing tree-shaped district heating network given a number of potential new consumers. To this end, we state a stationary and nonlinear model of all hydraulic and thermal effects in the pipeline network as well as nonlinear models for consumers and the … Read more
The thermal unit commitment (UC) problem often can be formulated as a mixed integer quadratic programming (MIQP), which is difficult to solve efficiently, especially for large-scale instances. The tighter characteristic re-duces the search space, therefore, as a natural conse-quence, significantly reduces the computational burden. In the literature, many tightened formulations for single units with parts … Read more
In this paper, we study the convex quadratic optimization problem with indicator variables. For the bivariate case, we describe the convex hull of the epigraph in the original space of variables, and also give a conic quadratic extended formulation. Then, using the convex hull description for the bivariate case as a building block, we derive … Read more
We investigate the problem of exactly separating cover inequalities of maximum depth and we develop a pseudo-polynomial-time algorithm for this purpose. Compared to the standard method based on the maximum violation, computational experiments carried out on knapsack and multi-dimensional knapsack instances show that, with a cutting-plane method based on the maximum-depth criterion, we can optimize … Read more
The Double Row Layout Problem (DRLP) occurs in automated manufacturing environments, where machines arranged in a double-row layout, i.e. the machines are located on either side of a straight line corridor. The DRLP is how to minimize the total cost of transporting materials between machines. The problem is NP-Hard. In this paper, we give a … Read more
In critical node problems, the task is identify a small subset of so-called critical nodes whose deletion maximally degrades a network’s “connectivity” (however that is measured). Problems of this type have been widely studied, e.g., for limiting the spread of infectious diseases. However, existing approaches for solving them have typically been limited to networks having … Read more
We consider the least squares regression problem, penalized with a combination of the L0 and L2 norms (a.k.a. L0 L2 regularization). Recent work presents strong evidence that the resulting L0-based estimators can outperform popular sparse learning methods, under many important high-dimensional settings. However, exact computation of L0-based estimators remains a major challenge. Indeed, state-of-the-art mixed … Read more
Traffic jams cause economical damage which has been estimated between 10 and 100 billion Euros per year in Germany, also due to inefficient urban traffic. It is currently open how the situation will change with upcoming technological advances in autonomous and electric mobility. On the one hand, autonomous cars may lead to an increased number … Read more
This paper investigates the estimation of the size of Branch-and-Bound (B&B) trees for solving mixed-integer programs. We first prove that the size of the B&B tree cannot be approximated within a factor of~2 for general binary programs, unless P equals NP. Second, we review measures of the progress of the B&B search, such as the … Read more
We develop a dual decomposition of two-stage distributionally robust mixed-integer programming (DRMIP) under the Wasserstein ambiguity set. The dual decomposition is based on the Lagrangian dual of DRMIP, which results from the Lagrangian relaxation of the nonanticipativity constraints and min-max inequality. We present two Lagrangian dual problem formulations, each of which is based on different principle. We show … Read more