The static bike rebalancing problem with optimal user incentives

Yanfeng Li and Yang Liu

Transportation Research Part E: Logistics and Transportation Review, 2021, vol. 146, issue C

Abstract: A static bike rebalancing problem with optimal user incentives is investigated. The problem is formulated as a mixed-integer nonlinear and nonconvex programming model to minimize the total cost, including the travel costs, unbalanced penalties, and incentive costs. We reformulate the mixed-integer program and develop a new outer-approximation method to obtain its global ε-optimal solutions. We also propose a bi-level variable neighborhood search algorithm to solve large problems. The results tested on small examples reveal problem properties and the performance of the outer-approximation method. The results tested on large examples show that the bi-level algorithm can provide high-quality solutions with short computational times.

Keywords: Bike rebalancing problem; User incentives; Outer-approximation; Variable neighborhood search (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.tre.2020.102216

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