Information Sciences: an International Journal
Information Sciences: an International Journal
An ant-based technique for the dynamic generalized traveling salesman problem
ISTASC'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Systems Theory and Scientific Computation - Volume 7
A new approach to generalized network design problems
EHAC'07 Proceedings of the 6th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications
Solving traveling salesman problem on cluster compute nodes
WSEAS Transactions on Computers
Effective neighborhood structures for the generalized traveling salesman problem
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
Hybrid chromosome genetic algorithm for generalized traveling salesman problems
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Editorial: The traveling salesman problem
Discrete Optimization
Transformations of generalized ATSP into ATSP
Operations Research Letters
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The Generalized Traveling Salesman Problem (GTSP) is an extension of the well known Traveling Salesman Problem (TSP). The GTSP is defined on a graph in which the nodes (customers or vertices) are grouped into a given number of clusters (node sets). Solution procedures for the GTSP are generally focused on transforming the problem to the TSP and applying the exact or heuristic solution methods developed for the TSP. There exist a few integer programming formulations for the GTSP some of which are exponential size with respect to number of the nodes. In this paper, we propose two new formulations for the GTSP with polynomial size with respect to number of the nodes. For preliminary computational analysis, GTSP instances from TSPLIB are solved by proposed formulations and also by the previously existing formulations in the literature. Performances of the formulations in terms of linear programming relaxations and CPU times are analyzed. We observe that, performances of the proposed formulations are better than the existing formulations in terms of these two evaluation criteria.