Integer linear programming formulations for the minimum connectivity inference problem and model reduction principles

The minimum connectivity inference (MCI) problem represents an NP-hard generalization of the well-known minimum spanning tree problem. Given a set of vertices and a finite collection of subsets (of this vertex set), the MCI problem requires to find an edge set of minimal cardinality so that the vertices of each subset are connected. Although the … Read more

A Stochastic Bin Packing Approach for Server Consolidation with Conflicts

The energy consumption of large-scale data centers or server clusters is expected to grow significantly in the next couple of years contributing to up to 13 percent of the worlwide energy demand in 2030. As the involved processing units require a disproportional amount of energy when they are idle, underutilized or overloaded, balancing the supply … Read more

Improved Flow-based Formulations for the Skiving Stock Problem

Thanks to the rapidly advancing development of (commercial) MILP software and hardware components, pseudo-polynomial formulations have been established as a powerful tool for solving cutting and packing problems in recent years. In this paper, we focus on the one-dimensional skiving stock problem (SSP), where a given inventory of small items has to be recomposed to … Read more

An Improved Flow-based Formulation and Reduction Principles for the Minimum Connectivity Inference Problem

The Minimum Connectivity Inference (MCI) problem represents an NP-hard generalisation of the well-known minimum spanning tree problem and has been studied in different fields of research independently. Let an undirected complete graph and finitely many subsets (clusters) of its vertex set be given. Then, the MCI problem is to find a minimal subset of edges … Read more