Stochastic fleet deployment models for public bicycle rental systems |
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Authors: | Shangyao Yan Min-Hung Wang |
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Institution: | Department of Civil Engineering, National Central University, Taoyuan, Taiwan |
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Abstract: | This paper presents two stochastic bike deployment (SBD) models that determine the optimal number of bicycles allocated to each station in a leisure-oriented public bicycle rental system with stochastic demands. The SBD models represent the stochastic demands using a set of scenarios with given probabilities. A multilayer bike-flow time-space network is constructed for developing the models, where each layer corresponds to a given demand scenario and effectively describes bicycle flows in the spatial and temporal dimensions. As a result, the models are formulated as the integer multi-commodity network flow problem, which is characterized as NP-hard. We propose a heuristic to efficiently obtain good quality solutions for large-size model instances. Test instances are generated using real data from a bicycle rental system in Taiwan to evaluate the performance of the models and the solution algorithm. The test results show that the models can help the system operator of a public bicycle system make effective fleet deployment decisions. |
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Keywords: | Bicycle rental fleet allocation multi-commodity network flows public bicycles time-space networks |
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