A target-based optimization model for bike-sharing systems: From the perspective of service efficiency and equity
The emergence of bike-sharing systems has considerably improved last- and first-mile transportation 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.
|ESI Research Field|
Cited Times [WOS]:0
|Document Type||Journal Article|
|Department||School of Business|
1.Institute of Systems Engineering, College of Management and Economics, Tianjin University, Tianjin 300072, China
2.Laboratory of Computation and Analytics of Complex Management Systems (CACMS), Tianjin University, Tianjin 300072, China
3.Institute of Operations Research and Analytics, National University of Singapore, Singapore 117602, Singapore
4.School of Business, Southern University of Science and Technology, Shenzhen 518055, China
Qingxin,Chen,Chenyi,Fu,Ning,Zhu,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.
Qingxin,Chen,Chenyi,Fu,Ning,Zhu,Shoufeng,Ma,&Qiao-Chu,He.(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.
Qingxin,Chen,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.
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