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A Randomized Granular Tabu Search heuristic for the split delivery vehicle routing problem

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  • Leonardo Berbotto
  • Sergio García
  • Francisco Nogales

Abstract

The Split Delivery Vehicle Routing Problem (SDVRP) is a variant of the classical Capacitated Vehicle Routing Problem where multiple visits to each customer are allowed. It is an NP-hard problem where exact solutions are difficult to obtain in a reasonable time. This paper shows a tabu search heuristic with granular neighborhood called Randomized Granular Tabu Search that uses a tabu search technique in a bounded neighborhood (granular) defined by the most promising arcs and introduces some new local operators in the local granular tabu search. The algorithm also uses a random selection of the move to be introduced at the current solution. In addition, the local search procedures can explore infeasible neighborhoods in terms of vehicle capacity. These two ideas help to escape from local optima. After the local search process, the algorithm solves one traveling salesman problem per route to improve the solution. Finally, a computational study shows that the proposed method improves many of the best-known solutions for the benchmark instances of the SDVRP literature. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Leonardo Berbotto & Sergio García & Francisco Nogales, 2014. "A Randomized Granular Tabu Search heuristic for the split delivery vehicle routing problem," Annals of Operations Research, Springer, vol. 222(1), pages 153-173, November.
    • Handle: RePEc:spr:annopr:v:222:y:2014:i:1:p:153-173:10.1007/s10479-012-1282-3
    DOI: 10.1007/s10479-012-1282-3
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    Cited by:

    1. Yangkun Xia & Zhuo Fu & Sang-Bing Tsai & Jiangtao Wang, 2018. "A New TS Algorithm for Solving Low-Carbon Logistics Vehicle Routing Problem with Split Deliveries by Backpack—From a Green Operation Perspective," IJERPH, MDPI, vol. 15(5), pages 1-12, May.
    2. Goeke, Dominik, 2019. "Granular tabu search for the pickup and delivery problem with time windows and electric vehicles," European Journal of Operational Research, Elsevier, vol. 278(3), pages 821-836.
    3. Bortfeldt, Andreas & Yi, Junmin, 2020. "The Split Delivery Vehicle Routing Problem with three-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 282(2), pages 545-558.
    4. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    5. Jianli Shi & Jin Zhang & Kun Wang & Xin Fang, 2018. "Particle Swarm Optimization for Split Delivery Vehicle Routing Problem," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(02), pages 1-42, April.
    6. Gizem Ozbaygin & Oya Karasan & Hande Yaman, 2018. "New exact solution approaches for the split delivery vehicle routing problem," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(1), pages 85-115, March.
    7. Han, Anthony Fu-Wha & Chu, Yu-Ching, 2016. "A multi-start heuristic approach for the split-delivery vehicle routing problem with minimum delivery amounts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 11-31.
    8. Yuxin Liu & Zihang Qin & Jin Liu, 2023. "An Improved Genetic Algorithm for the Granularity-Based Split Vehicle Routing Problem with Simultaneous Delivery and Pickup," Mathematics, MDPI, vol. 11(15), pages 1-15, July.
    9. Michael Schneider & Maximilian Löffler, 2019. "Large Composite Neighborhoods for the Capacitated Location-Routing Problem," Service Science, INFORMS, vol. 53(1), pages 301-318, February.
    10. Yangkun Xia & Zhuo Fu & Lijun Pan & Fenghua Duan, 2018. "Tabu search algorithm for the distance-constrained vehicle routing problem with split deliveries by order," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-19, May.

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