Information Sciences: an International Journal
Information Sciences: an International Journal
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
A new approach for solving the generalized traveling salesman problem
HM'10 Proceedings of the 7th international conference on Hybrid metaheuristics
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
A hybrid heuristic approach for solving the generalized traveling salesman problem
Proceedings of the 13th annual conference on Genetic and evolutionary computation
New formulations for the generalized traveling salesman problem
ASM'12 Proceedings of the 6th international conference on Applied Mathematics, Simulation, Modelling
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We consider the generalized traveling salesman problem in which a graph with nodes partitioned into clusters is given. The goal is to identify a minimum cost round trip visiting exactly one node from each cluster. For solving difficult instances of this problem heuristically, we present a new Variable Neighborhood Search (VNS) approach that utilizes two complementary, large neighborhood structures. One of them is the already known generalized 2-opt neighborhood for which we propose a new incremental evaluation technique to speed up the search significantly. The second structure is based on node exchanges and the application of the chained Lin-Kernighan heuristic. A comparison with other recently published metaheuristics on TSPlib instances with geographical clustering indicates that our VNS, though requiring more time than two genetic algorithms, is able to find substantially better solutions.