A target-based optimization model for bike-sharing systems: From the perspective of service efficiency and equity

Chen, Qingxin1,2; Fu, Chenyi3; Zhu, Ning1; Ma, Shoufeng1,2; He, Qiao-Chu4

2023

10.1016/j.trb.2022.12.002

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL   影响因子和分区

0191-2615

1879-2367

The emergence of bike-sharing systems has considerably improved last-and first-mile trans-portation systems. To ensure attractiveness to end users, operators aim to design effective service-oriented operational strategies to meet the desired service targets for users. Most existing studies focus on the service efficiency of bike-sharing systems, while service equity is overlooked. In this study, we propose a target-based stochastic distributionally robust optimization (TSDRO) model that addresses both the efficiency and equity of the service level in docked bike-sharing systems under demand uncertainty. We first employ a dissatisfaction risk measure to jointly quantify the probability and magnitude of user dissatisfaction in a zone. Then, we apply a lexicographic-order approach to define the objective function to achieve equity of service among different zones. This lexicographic approach optimizes the worst-off individual and the second-worst zone in an iterative manner. To address demand ambiguity, we use a data-driven method to explore the relationship between the demand distribution and several exogenous factors, including weather and weekends, and then construct a scenario -based distributionally robust optimization model. Based on duality theory and linear decision approximation, this model can be reformulated as a tractable equivalent deterministic model, which can be solved via a bisection-search approach to optimality. Numerical experiments based on real operational data show that compared with the benchmark models, the TSDRO model achieves (i) better out-of-sample performance in terms of service efficiency and (ii) higher service equity among users in different zones. Moreover, setting a lower target level may generate a better solution.

Bike-sharing service Equity Risk measure Stochastic distributionally robust optimization

SCI ; EI ; SSCI

英语

其他

National Natural Science Foundation of China["72122015","71971154","72010107004","72071101","72091210","72091214"] ; Shenzhen Natural Science Fund["GXWD20201230110313001","20200925160442005"]

Business & Economics ; Engineering ; Operations Research & Management Science ; Transportation

Economics ; Engineering, Civil ; Operations Research & Management Science ; Transportation ; Transportation Science & Technology

WOS:000992852300001

PERGAMON-ELSEVIER SCIENCE LTD

20225213291404

Benchmarking ; Bicycles ; Decision theory ; Iterative methods ; Optimization ; Risk assessment ; Stochastic models ; Stochastic systems

Passenger Highway Transportation:432.2 ; Control Systems:731.1 ; Production Engineering:913.1 ; Accidents and Accident Prevention:914.1 ; Optimization Techniques:921.5 ; Numerical Methods:921.6 ; Probability Theory:922.1 ; Systems Science:961

ENGINEERING

Web of Science

1.Tianjin Univ, Inst Syst Engn, Coll Management & Econ, Tianjin 300072, Peoples R China
2.Tianjin Univ, Lab Computat & Analyt Complex Management Syst CACM, Tianjin 300072, Peoples R China
3.Natl Univ Singapore, Inst Operat Res & Analyt, Singapore 117602, Singapore
4.Southern Univ Sci & Technol, Sch Business, Shenzhen 518055, Peoples R China

Chen, Qingxin,Fu, Chenyi,Zhu, Ning,et al. A target-based optimization model for bike-sharing systems: From the perspective of service efficiency and equity[J]. TRANSPORTATION RESEARCH PART B-METHODOLOGICAL,2023,167:235-260.

Chen, Qingxin,Fu, Chenyi,Zhu, Ning,Ma, Shoufeng,&He, Qiao-Chu.(2023).A target-based optimization model for bike-sharing systems: From the perspective of service efficiency and equity.TRANSPORTATION RESEARCH PART B-METHODOLOGICAL,167,235-260.

Chen, Qingxin,et al."A target-based optimization model for bike-sharing systems: From the perspective of service efficiency and equity".TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 167(2023):235-260.