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The static bike rebalancing problem with optimal user incentives

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  • Li, Yanfeng
  • Liu, Yang

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.

Suggested Citation

  • Li, Yanfeng & Liu, Yang, 2021. "The static bike rebalancing problem with optimal user incentives," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    • Handle: RePEc:eee:transe:v:146:y:2021:i:c:s1366554520308589
    DOI: 10.1016/j.tre.2020.102216
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