Optimization Strategies for Dockless Bike Sharing Systems via two Algorithms of Closed Queuing Networks
| Autor: | Fan-Qi Ma, Quan-Lin Li, Rui-Na Fan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
closed queuing network dockless bike sharing system Computer science Computation 0211 other engineering and technologies Bioengineering 02 engineering and technology lcsh:Chemical technology lcsh:Chemistry 020901 industrial engineering & automation Robustness (computer science) Telecommunications link Chemical Engineering (miscellaneous) lcsh:TP1-1185 sustainable transportation Subnetwork Queueing theory 021103 operations research Process Chemistry and Technology Queuing network flow equivalent server algorithm lcsh:QD1-999 Mean value analysis Bike sharing mean value analysis Algorithm optimization strategy |
| Zdroj: | Processes Volume 8 Issue 3 Processes, Vol 8, Iss 3, p 345 (2020) |
| ISSN: | 2227-9717 |
| DOI: | 10.3390/pr8030345 |
| Popis: | The dockless bike sharing system (DBSS) has been globally adopted as a sustainable transportation system. Due to the robustness and tractability of the closed queuing network (CQN), it is a well-behaved method to model DBSSs. In this paper, we view DBSSs as CQNs and use the mean value analysis (MVA) algorithm to calculate a small size DBSS and the flow equivalent server (FES) algorithm to calculate the larger size DBSS. This is the first time that the FES algorithm is used to study the DBSS, by which the CQN can be divided into different subnetworks. A parking region and its downlink roads are viewed as a subnetwork, so the computation of CQN is reduced greatly. Based on the computation results of the two algorithms, we propose two optimization functions for determining the optimal fleet size and repositioning flow, respectively. At last, we provide numerical experiments to verify the two algorithms and illustrate the optimal fleet size and repositioning flow. This computation framework can also be used to analyze other on-demand transportation networks. |
| Databáze: | OpenAIRE |
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