We present a new model for a strategic locomotive scheduling problem arising at the Deutsche Bahn AG. The model is based on a multi-commodity min-cost flow formulation that is also used for public bus scheduling problems. However, several new aspects have to be additionally taken into account, such as cyclic departures of the trains, time windows on starting and arrival times, network-load depe...

How difficult is, in practice, to optimize exactly over the first Chvátal closure of a generic ILP? Which fraction of the integrality gap can be closed this way, e.g., for some hard problems in the MIPLIB library? Does it pay to insist on rank-1 Chvátal-Gomory inequalities until no such inequality is violated, or one should better follow the usual strategy of generating (mixed-integer) Gomory c...

Abstract Inductive logic programming (ILP) is a form of logic-based machine learning. The goal to induce hypothesis (a program) that generalises given training examples and background knowledge. As ILP turns 30, we review the last decade research. We focus on (i) new meta-level search methods, (ii) techniques for learning recursive programs, (iii) approaches predicate invention, (iv) use differ...

Reliable site-specific delivery of genetic constructs remains a challenging component of gene-based therapy of solid tumors. Isolated limb perfusion (ILP) continues to be evaluated for treatment of locally advanced soft tissue sarcomas because this approach uniquely directs therapeutic agents into the tumor-bearing extremity without significant systemic leak. In light of these considerations, w...

AIM To improve tumor control in lung metastases using a novel method: unilateral chemoembolization of the lung by instillation of degradable starch microspheres (DSM) and cytotoxic agents via the pulmonal artery. MATERIALS AND METHODS A rodent model of solitary metastasis (CC531 adenocarcinoma) was studied. The animals were randomized into three groups: the control group receiving carboplatin...

Several central and well-known combinatorial problems in phylogenetics and population genetics have efficient, elegant solutions when the input is complete or consists of haplotype data, but lack efficient solutions when input is either incomplete, consists of genotype data, or is for problems generalized from decision questions to optimization questions. Unfortunately, in biological applicatio...

Reconciliation methods aim at recovering macro evolutionary events and at localizing them in the species history, by observing discrepancies between gene family trees and species trees. In this article we introduce an Integer Linear Programming (ILP) approach for the NP-hard problem of computing a most parsimonious time-consistent reconciliation of a gene tree with a species tree when dating in...

Some state-of-the-art summarization systems use integer linear programming (ILP) based methods that aim to maximize the important concepts covered in the summary. These concepts are often obtained by selecting bigrams from the documents. In this paper, we improve such bigram based ILP summarization methods from different aspects. First we use syntactic information to select more important bigra...

Motivation: There is an urgent need for automated methods to learn general features of the interactions of a ligand class with its diverse set of protein receptors. An appropriate machine learning approach is Inductive Logic Programming (ILP) which automatically generates comprehensible rules in addition to prediction. The development of ILP systems which can learn rules of the complexity requi...

In this thesis, we consider frequency assignment problems arising from an SDMA satellite communication system which consists of a satellite and a number of users distributed inside a fixed sized service area. The objective is to assign a given number of frequency carriers to as many users as possible. This assignment should not violate the incurred interference constraints. Two types of interfe...