Citation

Li Y, Liu Y. Transp. Res. E Logist. Transp. Rev. 2021; 146: e102216.

Copyright

(Copyright © 2021, Elsevier Publishing)

DOI

10.1016/j.tre.2020.102216

PMID

unavailable

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.

Language: en

Keywords

Bike rebalancing problem; Outer-approximation; User incentives; Variable neighborhood search