GLNS: an effective large neighborhood search heuristic for the generalized traveling salesman problem. This paper presents a new solver for the exactly one-in-a-set generalized traveling salesman problem (GTSP). In the GTSP, a complete directed graph with edge weights is given as input along with a partition of the vertices into disjoint sets. The objective is to find a cycle (or tour) in the graph that visits each set exactly once and has minimum length. In this paper, we present an effective algorithm for the GTSP based on an adaptive large neighborhood search. The algorithm operates by repeatedly removing from, and inserting vertices in the tour. We propose a general insertion mechanism that contains, as special cases, the well-known nearest, farthest and random insertion mechanisms. We provide extensive benchmarking results for our solver in comparison to the state-of-the-art on a wide range of existing and new problem libraries. We show that on the GTSP-LIB library, the proposed algorithm is competitive with the best known algorithms. On several other libraries. We show that given the same amount of time, the proposed solver finds higher quality solutions than existing approaches, particularly on harder instances that are non-metric and/or whose sets are not clustered.
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References in zbMATH (referenced in 4 articles , 1 standard article )
Showing results 1 to 4 of 4.
- Baniasadi, Pouya; Foumani, Mehdi; Smith-Miles, Kate; Ejov, Vladimir: A transformation technique for the clustered generalized traveling salesman problem with applications to logistics (2020)
- Drake, John H.; Kheiri, Ahmed; Özcan, Ender; Burke, Edmund K.: Recent advances in selection hyper-heuristics (2020)
- Yuan, Yuan; Cattaruzza, Diego; Ogier, Maxime; Semet, Frédéric: A branch-and-cut algorithm for the generalized traveling salesman problem with time windows (2020)
- Smith, Stephen L.; Imeson, Frank: GLNS: an effective large neighborhood search heuristic for the generalized traveling salesman problem (2017)