Determinants of Unlawful File Sharing: A Scoping Review

We employ a scoping review methodology to consider and assess the existing evidence on the determinants of unlawful file sharing (UFS) transparently and systematically. Based on the evidence, we build a simple conceptual framework to model the psychological decision to engage in UFS, purchase legally or do nothing. We identify social, moral, experiential, technical, legal and financial utility sources of the decision to purchase or to file share. They interact in complex ways. We consider the strength of evidence within these areas and note patterns of results. There is good evidence for influences on UFS within each of the identified determinants, particularly for self-reported measures, with more behavioral research needed. There are also indications that the reasons for UFS differ across media; more studies exploring media other than music are required

Solving the k-best traveling salesman problem

Although k-best solutions for polynomial solvable problems are extensively studied in the literature, not much is known for NP-hard problems. In this paper we design algorithms for finding sets of k-best solutions to the Traveling Salesman Problem (TSP) for some positive integer k. It will be shown that a set of k-best Hamiltonian tours in a weighted graph can be determined by applying the so-called partitioning algorithms and by algorithms based on modifications of solution methods like branch-and-bound. In order to study the effectiveness of these algorithms, the time for determining a set of k-best solutions is investigated for a number of instances in Reinelt's TSPLIB library. It appears that the time required to find a set of k-best tours grows rather slowly in k. Furthermore, the results of numerical experiments show that the difference in length between a longest and a shortest tour in the set of k-best solutions grows only slowly in k and that also the 'structure' of the tours in the set of k-best tours is quite robust. (C) 1999 Elsevier Science Ltd. All rights reserved.</p

Solving the k-best traveling salesman problem

Although k-best solutions for polynomial solvable problems are extensively studied in the literature, not much is known for NP-hard problems. In this paper we design algorithms for finding sets of k-best solutions to the Traveling Salesman Problem (TSP) for some positive integer k. It will be shown that a set of k-best Hamiltonian tours in a weighted graph can be determined by applying the so-called partitioning algorithms and by algorithms based on modifications of solution methods like branch-and-bound. In order to study the effectiveness of these algorithms, the time for determining a set of k-best solutions is investigated for a number of instances in Reinelt's TSPLIB library. It appears that the time required to find a set of k-best tours grows rather slowly in k. Furthermore, the results of numerical experiments show that the difference in length between a longest and a shortest tour in the set of k-best solutions grows only slowly in k and that also the 'structure' of the tours in the set of k-best tours is quite robust. (C) 1999 Elsevier Science Ltd. All rights reserved