Channel routing is a type of problems arising in the detailed routing phase of VLSI physical design automation as well as in the design of printed circuit boards (PCBs). It has been known that channel routing problems can be formulated as constraint programming (CP) problems and thus CP solvers can be used to find solutions. In this article, we present a mixed integer linear programming (MILP) ...

Plain vanilla K-means clustering is prone to produce unbalanced clusters and suffers from outlier sensitivity. To mitigate both shortcomings, we formulate a joint outlier-detection and clustering problem, which assigns a prescribed number of datapoints to an auxiliary outlier cluster and performs cardinality-constrained K-means clustering on the residual dataset. We cast this problem as a mixed...

In this paper the problem of finding the sparsest (i.e., minimum cardinality) critical k-tuple including one arbitrarily specified measurement is considered. The solution to this problem can be used to identify weak points in the measurement set, or aid the placement of new meters. The critical k-tuple problem is a combinatorial generalization of the critical measurement calculation problem. Us...

Upgradeability problems are a critical issue in modern operating systems. The problem consists in finding the “best” solution according to some criteria, to install, remove or upgrade packages in a given installation. This is a difficult problem: the complexity of the upgradeability problem is NP complete and modern OS contain a huge number of packages (often more than 20 000 packages in a Linu...

The paper focuses on the solution of the minimum loss reconfiguration problem of distribution networks, including embedded generation, by means of a mixed integer linear programming (MILP) model. The proposed model takes into account typical operating constraints of distribution networks (radial configuration, branch ampacity limits and bus voltage requirements). The accuracy of the results and...

We consider the application of mixed-integer linear programming (MILP) solvers to the minimization of submodular functions. We evaluate common large-scale linear-programming (LP) techniques (e.g., column generation, row generation, dual stabilization) for solving a LP reformulation of the submodular minimization (SM) problem. We present heuristics based on the LP framework and a MILP solver. We...

This work further elaborates on the steel plant MILP production scheduling method presented in Harjunkoski and Grossmann (2001). The proposed improvements include a more flexible model for the casting step, as well as combining orders from consecutive weeks to improve one of the main targets, which is increasing the number of heats per casting sequence. The paper presents a strategy to obtain o...