Petrica C. Pop

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We consider the Generalized Minimum Spanning Tree Problem denoted by GMSTP. It is known that GMSTP is NP-hard and even finding a near optimal solution is NP-hard. We introduce a new mixed integer programming formulation of the problem which contains a polynomial number of constraints and a polynomial number of variables. Based on this formulation we give an(More)
A well known N P-hard problem called the Generalized Traveling Salesman Problem (GTSP) is considered. In GTSP the nodes of a complete undirected graph are partitioned into clusters. The objective is to find a minimum cost tour passing through exactly one node from each cluster. An exact exponential time algorithm and an effective meta-heuristic algorithm(More)
Feedback can be described as a way to provide information on doctors' performance to enable changes in future behaviour. Feedback is used with the aim of changing test-ordering behaviour. It can lead to reductions in test usage and cost savings. It is not sufficiently clear, however, whether feedback leads to more appropriate test use. Since 1985, the(More)
We consider the Railway Traveling Salesman Problem (RTSP) in which a salesman using the railway network wishes to visit a certain number of cities to carry out his/her business, starting and ending at the same city, and having as goal to minimize the overall time of the journey. RTSP is an N P-hard problem. Although it is related to the Generalized(More)
The generalized traveling salesman problem (GTSP) is an NP-hard problem that extends the classical traveling salesman problem by partitioning the nodes into clusters and looking for a minimum Hamiltonian tour visiting exactly one node from each cluster. In this paper, we combine the consultant-guided search technique with a local-global approach in order to(More)
Given a complete undirected graph with the nodes partitioned into m node sets called clusters, the Generalized Minimum Spanning Tree problem denoted by GMST is to find a minimum-cost tree which includes exactly one node from each cluster. It is known that the GMST problem is NP-hard and even finding a near optimal solution is NP-hard. We give an(More)
The idea of sensitivity in ant colony systems has been exploited in hybrid ant-based models with promising results for many combinatorial optimization problems. Heterogeneity is induced in the ant population by endowing individual ants with a certain level of sensitivity to the pheromone trail. The variable pheromone sensitivity within the same population(More)