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The traveling salesman problem is one of the most famous combina-torial optimization problems, and has been intensively studied in the last decades. Many extensions to the basic problem have been also proposed, with the aim of making the resulting mathematical models as much realistic as possible. We present a new extension to the basic problem, where(More)
We study a version of the traveling salesman problem where travel times are specified as a range of possible values. This model reflects the difficulties to estimate travel times exactly in reality. Robustness concepts are used to drive optimization. We propose some efficient heuristic and preprocessing techniques. Computational experiments are presented.
land (SUPSI), and was founded in 1988 by the Dalle Molle Foundation which promoted quality of life. Abstract In this paper we deal with a new probabilistic extension of the Minimum Power Multi-cast (MPM) problem for wireless networks. The deterministic MPM problem consists in assigning transmission powers to the nodes, so that a multihop connection can be(More)
In this paper we describe some results on the linear integer programming formulation of the Probabilistic Minimum Power Multicast (PMPM) problem for wireless networks. The PMPM problem consists in optimally assigning transmission powers to the nodes of a given network in order to establish a multihop connection between a source node and a set of destination(More)
The Maximum Permutation Code Problem (MPCP) is a well-known combinatorial optimization problem in coding theory. The aim is to generate the largest possible permutation codes, having a given length n and a minimum Hamming distance d between the codewords. In this paper we present a new branch and bound algorithm, which combines combinatorial techniques with(More)
This study analyzes the transportation network of a major rail freight operator in order to obtain a model of delay propagation of trains connecting intermodal terminals. Operational management of a rail freight operator needs to take into account deviations due to unexpected events such as unplanned maintenance, strikes, railroad works, traffic congestion.(More)
This work presents an approach to the Maximum Permutation Code Problem (MPCP) that exploits the orbits of permutation groups in a new way. Several scientific works of recent years studied the principle of building feasible codes by combining the orbits of single permutation groups. However, the idea of combining orbits stemming from more than one group has(More)
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