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A hybrid large neighborhood search for the static multi-vehicle bike-repositioning problem

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  • Ho, Sin C.
  • Szeto, W.Y.

Abstract

This paper addresses the multi-vehicle bike-repositioning problem, a pick-up and delivery vehicle routing problem that arises in connection with bike-sharing systems. Bike-sharing is a green transportation mode that makes it possible for people to use shared bikes for travel. Bikes are retrieved and parked at any of the stations within the bike-sharing network. One major challenge is that the demand for and supply of bikes are not always matched. Hence, vehicles are used to pick up bikes from surplus stations and transport them to deficit stations to satisfy a particular service level. This operation is called a bike-repositioning problem. In this paper, we propose a hybrid large neighborhood search for solving the problem. Several removal and insertion operators are proposed to diversify and intensify the search. A simple tabu search is further applied to the most promising solutions. The heuristic is evaluated on three sets of instances with up to 518 stations and five vehicles. The results of computational experiments indicate that the heuristic outperforms both CPLEX and the math heuristic proposed by Forma et al. (2015) [Transportation Research Part B 71: 230–247]. The average improvement of our heuristic over the math heuristic is 1.06%, and it requires only a small fraction of the computation time.

Suggested Citation

  • Ho, Sin C. & Szeto, W.Y., 2017. "A hybrid large neighborhood search for the static multi-vehicle bike-repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 340-363.
  • Handle: RePEc:eee:transb:v:95:y:2017:i:c:p:340-363
    DOI: 10.1016/j.trb.2016.11.003
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    References listed on IDEAS

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    1. Li, Yanfeng & Szeto, W.Y. & Long, Jiancheng & Shui, C.S., 2016. "A multiple type bike repositioning problem," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 263-278.
    2. Tal Raviv & Ofer Kolka, 2013. "Optimal inventory management of a bike-sharing station," IISE Transactions, Taylor & Francis Journals, vol. 45(10), pages 1077-1093.
    3. Stefan Ropke & David Pisinger, 2006. "An Adaptive Large Neighborhood Search Heuristic for the Pickup and Delivery Problem with Time Windows," Transportation Science, INFORMS, vol. 40(4), pages 455-472, November.
    4. Lin, Jenn-Rong & Yang, Ta-Hui, 2011. "Strategic design of public bicycle sharing systems with service level constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(2), pages 284-294, March.
    5. Alvarez-Valdes, Ramon & Belenguer, Jose M. & Benavent, Enrique & Bermudez, Jose D. & Muñoz, Facundo & Vercher, Enriqueta & Verdejo, Francisco, 2016. "Optimizing the level of service quality of a bike-sharing system," Omega, Elsevier, vol. 62(C), pages 163-175.
    6. Erdoğan, Güneş & Battarra, Maria & Wolfler Calvo, Roberto, 2015. "An exact algorithm for the static rebalancing problem arising in bicycle sharing systems," European Journal of Operational Research, Elsevier, vol. 245(3), pages 667-679.
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    8. Ho, Sin C. & Szeto, W.Y., 2014. "Solving a static repositioning problem in bike-sharing systems using iterated tabu search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 180-198.
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