期刊：
Journal of Advanced Transportation,2020年2020 ISSN：0197-6729
通讯作者：
Fu, Zhuo
作者机构：
[Tang, Qiong; Fu, Zhuo; Zhang, Dezhi] Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;[Tang, Qiong] Hengyang Normal Univ, Coll Econ & Management, Hengyang 421002, Peoples R China.;[Tang, Qiong; Fu, Zhuo; Zhang, Dezhi] Smart Transport Key Lab Hunan Prov, Changsha 410075, Peoples R China.;[Qiu, Meng] Chinese Univ Hong Kong, Inst Data & Decis Analyt, Shenzhen 518172, Peoples R China.;[Li, Minyi] RMIT Univ, Sch Sci, Melbourne, Vic 3000, Australia.
通讯机构：
[Fu, Zhuo] C;[Fu, Zhuo] S;Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;Smart Transport Key Lab Hunan Prov, Changsha 410075, Peoples R China.
摘要：
In this paper, a single-vehicle static partial repositioning problem (SPRP) is investigated, which distinguishes the user dissatisfaction generated by different stations. The overall objective of the SPRP is to minimize the weighted sum of the total operational time and the total absolute deviation from the target number of bikes at all stations. An iterated local search is developed to solve this problem. A novel loading and unloading quantity adjustment operator is proposed to further improve the quality of the solution. Experiments are conducted on a set of instances from 30 to 300 stations to demonstrate the effectiveness of the proposed customized solution algorithm as well as the adjustment operator. Using a small example, this paper also reveals that the unit penalty cost has an effect on the repositioning strategies.
作者机构：
[Tang, Qiong; Fu, Zhuo; Zhang, Dezhi] Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;[Tang, Qiong] Hengyang Normal Univ, Coll Econ & Management, Hengyang 421002, Peoples R China.;[Tang, Qiong; Fu, Zhuo; Zhang, Dezhi] Smart Transport Key Lab Hunan Prov, Changsha 410075, Peoples R China.;[Guo, Hao] Jinan Univ, Sch Management, Guangzhou 510632, Peoples R China.;[Li, Minyi] RMIT Univ, Sch Sci, Melbourne, Vic 3000, Australia.
通讯机构：
[Fu, Zhuo] C;[Fu, Zhuo] S;Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;Smart Transport Key Lab Hunan Prov, Changsha 410075, Peoples R China.
摘要：
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. 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.
