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TSP with Multiple Time-Windows and Selective Cities

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Computational Logistics (ICCL 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8197))

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Abstract

We address a special TSP in which the set of cities is partitioned into two subsets: mandatory cities and selective cities. All mandatory cities should be visited once within one of the corresponding predefined multiple time windows. A subset of the selective cities, whose cardinality depends on the tour completion time, should be visited within one of the associated multiple time windows. The objective is to plan a tour, not exceeding a predefined number of days, that minimizes a linear combination of the total traveled distance as well as the total waiting time. We present a mixed integer linear programming (MILP) model for the problem and propose a heuristic approach to solve it. Computational experiments address two real world problems that arise in different practical contexts.

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References

  1. Fischetti, M., Salazar-González, J.-J., Toth, P.: The generalized traveling salesman and orienteering problems. In: Gutin, G., Punnen, A.P. (eds.) The Traveling Salesman Problem and its Variants, pp. 609–662. Kluwer (2002)

    Google Scholar 

  2. Gendreau, M., Laporte, G., Semet, F.: A branch-and-cut algorithm for the undirected selective traveling salesman problem. Networks 32(4), 263–273 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kaufman, L., Rousseeuw, P.J.: Finding groups in data: an introduction to cluster analysis. Wiley, New York (1990)

    Book  Google Scholar 

  4. Labadie, N., Mansini, R., Melechovsky, J., Calvo, R.W.: The team orienteering problem with time windows: An LP-based granular variable neighborhood search. European Journal of Operational Research 220, 15–27 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  5. Pisinger, D., Ropke, S.: A general heuristic for vehicle routing problems. Computers & Operations Research 34, 2403–2435 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  6. Ropke, S., Pisinger, D.: An adaptative large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Science 40(4), 455–472 (2006)

    Article  Google Scholar 

  7. Tricoire, F., Romauch, M., Doerner, K.F., Hartl, R.F.: Heuristics for the multi-period orienteering problem with multiple time windows. Computers & Operations Research 37, 351–367 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  8. Vansteenwegen, P., Souffriau, W., Berghe, G.V., Oudheusden, D.V.: Iterated local search for the team orienteering problem with time windows. Computers & Operations Research 36, 3281–3290 (2009)

    Article  MATH  Google Scholar 

  9. Vansteenwegen, P., Souffriau, W., Oudheusden, D.V.: The orienteering problem: A survey. European Journal of Operational Research 209, 1–10 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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Mesquita, M., Murta, A., Paias, A., Wise, L. (2013). TSP with Multiple Time-Windows and Selective Cities. In: Pacino, D., Voß, S., Jensen, R.M. (eds) Computational Logistics. ICCL 2013. Lecture Notes in Computer Science, vol 8197. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41019-2_12

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  • DOI: https://doi.org/10.1007/978-3-642-41019-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-41018-5

  • Online ISBN: 978-3-642-41019-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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