Abstract
In this paper, a bike repositioning problem with stochastic demand is studied. The problem is formulated as a two-stage stochastic programming model to optimize the routing and loading/unloading decisions of the repositioning truck at each station and depot under stochastic demands. The goal of the model is to minimize the expected total sum of the transportation costs, the expected penalty costs at all stations, and the holding cost of the depot. A simulated annealing algorithm is developed to solve the model. Numerical experiments are conducted on a set of instances from 20 to 90 stations to demonstrate the effectiveness of the solution algorithm and the accuracy of the proposed two-stage stochastic model.
Highlights
Bike sharing system (BSS) as a means of sustainable and carbon-free transportation can effectively solve the “the first and last mile” problem of urban public transportation
To ensure the availability of bikes at all stations in the system, the BSS needs to employ redistribution trucks to transfer bikes from stations to stations, to balance the number of bikes according to the demand in each station. is problem is commonly defined as the bike repositioning problem (BRP) in the BSS. e main objective of the BRP is to balance the supply and demand of bikes across stations as a mean to improve user satisfaction, while in the meantime, to reduce the transportation cost of redistribution trucks as much as possible
We briefly review studies that are related to this paper, including heuristic and metaheuristic solution methods, for solving the deterministic BRP and models for the BRP with stochastic demands
Summary
Bike sharing system (BSS) as a means of sustainable and carbon-free transportation can effectively solve the “the first and last mile” problem of urban public transportation. E main objective of the BRP is to balance the supply and demand of bikes across stations as a mean to improve user satisfaction, while in the meantime, to reduce the transportation cost of redistribution trucks as much as possible. Some bikes can be picked up from the depot to meet the demand of bike deficient stations, and/or some bikes at bike surplus stations can be brought back to the depot, in order to achieve a perfect balance between supply and demand at all stations in the BSS [4,5,6,7] These existing works have not yet considered the holding cost of the depot in the BRP model.
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