A dynamic scheduling method via predicted inventory variation rate for public bicycle(PDF)
长安大学学报（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]
- Issue:
- 2019年06期
- Page:
- 108-115
- Research Field:
- 交通工程
- Publishing date:
Info
- Title:
- A dynamic scheduling method via predicted inventory variation rate for public bicycle
- Author(s):
- GAO Liang; XU Wei
- (1. Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China; 2. National Railway Track Test Center, China Academy of Railway Sciences Corporation Limited, Beijing 100015, China)
- Keywords:
- traffic engineering; dynamic scheduling; mixed integer programming; public bicycle system; inventory variation rate
- PACS:
- -
- DOI:
- -
- Abstract:
- To improve the efficiency and reduce the scheduling cost of public bicycle system, a dynamic scheduling scheme based on the predicted inventory variation rate was proposed. Each public bicycle station was regarded as an inventory system, the inventory variation rate of each station during the scheduling period and the inventory rate of each station at the end of the scheduling period were predicted based on the stationary distribution of Markov Process. Considering the reasonable interval of inventory rate of each station, the stations which should be rebalanced were determined based on the initial inventory rate and the predicted inventory rate of each station. The dynamic scheduling problem (DSP) was addressed, in which a capacitated dispatching vehicle was employed to redistribute the bikes in terms of the latest arrival time of each station with the objective of minimizing total scheduling distance. The DSP model was solved by the Simulated Annealing Algorithm, and got the optimal scheduling scheme. Because the inventory variation rate of each station were predicted, for a given scheduling area, the dispatching vehicle cruised only once, which could enable the inventory rate of each station to stay in a reasonable interval from the time it was served to the end of scheduling period. Bluebikes (Boston, MA, USA) public bicycle system was taken as an example, the dynamic scheduling scheme based on predicted inventory variation rate was validated. The results show that the dynamic scheduling scheme based on the predicted inventory variation rate could at most shorten the cruise distance of the dispatching vehicle by 35.58% among all scheduling areas, and could shorten the total cruise distance of all dispatching vehicles by 18.53% for the whole Bluebikes public bicycle system. Compared with the rolling scheduling horizon, the proposed scheme avoids the passive adjustment of the scheduling scheme without the piecewise detection of the system operation state, and improves the efficiency of the generation and execution of the scheduling scheme. 3 tabs, 4 figs, 26 refs.
Last Update: 2019-12-19