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An iterated local search algorithm for the Travelling Salesman Problem with Pickups and Deliveries

Author

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  • A Subramanian

    (Universidade Federal da Paraíba, João Pessoa, Brazil)

  • M Battarra

    (University of Southampton, Southampton, UK)

Abstract

The Travelling Salesman Problem with Pickups and Deliveries (TSPPD) consists in designing a minimum cost tour that starts at the depot, provides either a pickup or delivery service to each of the customers and returns to the depot, in such a way that the vehicle capacity is not exceeded in any part of the tour. In this paper, the TSPPD is solved by considering a metaheuris-tic algorithm based on Iterated Local Search with Variable Neighbourhood Descent and Random neighbourhood ordering. Our aim is to propose a fast, flexible and easy to code algorithm, also capable of producing high quality solutions. The results of our computational experience show that the algorithm finds or improves the best known results reported in the literature within reasonable computational time.

Suggested Citation

  • A Subramanian & M Battarra, 2013. "An iterated local search algorithm for the Travelling Salesman Problem with Pickups and Deliveries," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(3), pages 402-409, March.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:3:p:402-409
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    Cited by:

    1. Roel G. van Anholt & Leandro C. Coelho & Gilbert Laporte & Iris F. A. Vis, 2016. "An Inventory-Routing Problem with Pickups and Deliveries Arising in the Replenishment of Automated Teller Machines," Transportation Science, INFORMS, vol. 50(3), pages 1077-1091, August.
    2. Arthur Kramer & Anand Subramanian, 2019. "A unified heuristic and an annotated bibliography for a large class of earliness–tardiness scheduling problems," Journal of Scheduling, Springer, vol. 22(1), pages 21-57, February.

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