Joint Pricing, Operational Planning and Routing Design of a Fixed-Route Ride-sharing Service

Data-driven demand model;Nonlinear optimization;Mixed integer linear programming;Route design;Genetic algorithm;Industrial and operations engineering;Industrial and Systems Engineering, College of Engineering & Computer Science

Zhu, WanqingHu, Jian ;

University of Michigan

关键词: Data-driven demand model;    Nonlinear optimization;    Mixed integer linear programming;    Route design;    Genetic algorithm;    Industrial and operations engineering;    Industrial and Systems Engineering, College of Engineering & Computer Science;   

Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/146788/49698122_Wanqing%27s%20Graduate%20Thesis%20%28final%29.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: The Illinois Digital Environment for Access to Learning and Scholarship

【 摘 要 】

Fixed-route ride-sharing services are becoming increasing popular among major metropolitan areas, e.g., Chariot, OurBus, Boxcar. Effective routing design and pricing and operational planning of these services are undeniably crucial in their profitability and survival. However, the effectiveness of existing approaches have been hindered by the accuracy in demand estimation. In this paper, we develop a demand model using the multinomial logit model. We also construct a nonlinear optimization model based on thisdemand model to jointly optimize price and operational decisions. Moreover, we develop a mixed integer linear optimization model to the routing design decision. And a geneticalgorithm based approach is proposed to solve the optimization model. Two case studies based on a real world fixed-route ride-sharing service are presented to demonstrate howthe proposed models are used to improve the profitability of the service respectively. We also show how this model can apply in settings where only limited public data are available to obtain effective estimation of demand and profit.