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A novel approach for designing rental vehicle repositioning strategies

Author

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  • Debjit Roy
  • Jennifer A. Pazour
  • René de Koster

Abstract

An important tactical decision for vehicle rental providers is the design of a repositioning strategy to balance vehicle utilization with customer wait times due to vehicle unavailabilities. To address this problem, this article analyzes alternative repositioning strategies: a no-repositioning strategy, a customer repositioning strategy, and a vehicle repositioning strategy, using queuing network models that are able to handle stochastic demand and vehicle unavailabilities. Optimization models are formulated to determine the repositioning fractions for alternate strategies that minimize the rental provider’s cost by balancing repositioning costs with customer waiting penalty costs. The nonlinear optimization problems are challenging to solve because the objective functions are non-differentiable and the decision variables (such as effective arrival rates and customer repositioning fractions) are interrelated. Therefore, a two-phase sequential solution approach to estimate the repositioning fractions is developed. Phase 1 determines the effective arrival rates by developing an approximate network model, deriving structural results, determining a high-quality solution point, and refining the solution. Phase 2 determines the repositioning fractions by solving a transportation problem. Numerical experiments are used to evaluate the efficacy of the proposed solution approach, to analyze alternate repositioning strategies, and to illustrate how the developed techniques can be adopted to create a better readiness at a depot.

Suggested Citation

  • Debjit Roy & Jennifer A. Pazour & René de Koster, 2014. "A novel approach for designing rental vehicle repositioning strategies," IISE Transactions, Taylor & Francis Journals, vol. 46(9), pages 948-967, September.
  • Handle: RePEc:taf:uiiexx:v:46:y:2014:i:9:p:948-967
    DOI: 10.1080/0740817X.2013.876129
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    Cited by:

    1. Nishant Mishra & Debjit Roy & Jan-Kees van Ommeren, 2017. "A Stochastic Model for Interterminal Container Transportation," Transportation Science, INFORMS, vol. 51(1), pages 67-87, February.
    2. Bansal, Vishal & Kumar, Deepak Prakash & Roy, Debjit & Subramanian, Shankar C., 2022. "Performance evaluation and optimization of design parameters for electric vehicle-sharing platforms by considering vehicle dynamics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
    3. Liu, Yang & Wu, Fanyou & Lyu, Cheng & Li, Shen & Ye, Jieping & Qu, Xiaobo, 2022. "Deep dispatching: A deep reinforcement learning approach for vehicle dispatching on online ride-hailing platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 161(C).

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