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A k-level data structure for large-scale traveling salesman problems

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Listed:
  • Colin Osterman

    (University of Mississippi)

  • César Rego

    (University of Mississippi)

Abstract

The problem of data representation is fundamental to the efficiency of search algorithms for the traveling salesman problem (TSP). The computational effort required to perform such tour operations as traversal and subpath reversal considerably influence algorithm design and performance. We propose a new data structure—the k-level satellite tree—for representing a TSP tour with a discussion of properties in the framework of general tour operations. The k-level satellite tree representation is shown to be significantly more efficient than its predecessors for large-scale instances.

Suggested Citation

  • Colin Osterman & César Rego, 2016. "A k-level data structure for large-scale traveling salesman problems," Annals of Operations Research, Springer, vol. 244(2), pages 583-601, September.
    • Handle: RePEc:spr:annopr:v:244:y:2016:i:2:d:10.1007_s10479-016-2159-7
    DOI: 10.1007/s10479-016-2159-7
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    References listed on IDEAS

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    1. Buyang Cao & Fred Glover, 1997. "Tabu Search and Ejection Chains---Application to a Node Weighted Version of the Cardinality-Constrained TSP," Management Science, INFORMS, vol. 43(7), pages 908-921, July.
    2. César Rego, 1998. "A Subpath Ejection Method for the Vehicle Routing Problem," Management Science, INFORMS, vol. 44(10), pages 1447-1459, October.
    3. S. Lin & B. W. Kernighan, 1973. "An Effective Heuristic Algorithm for the Traveling-Salesman Problem," Operations Research, INFORMS, vol. 21(2), pages 498-516, April.
    4. Rego, Cesar, 1998. "Relaxed tours and path ejections for the traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 522-538, April.
    5. Gamboa, Dorabela & Rego, Cesar & Glover, Fred, 2005. "Data structures and ejection chains for solving large-scale traveling salesman problems," European Journal of Operational Research, Elsevier, vol. 160(1), pages 154-171, January.
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