Optimizing the Profitability and Quality of Service in Carshare Systems Under Demand Uncertainty

37 Pages Posted: 27 Jun 2017

See all articles by Mengshi Lu

Mengshi Lu

Purdue University - Krannert School of Management

Zhihao Chen

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Siqian Shen

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Date Written: March 30, 2017

Abstract

Carsharing has been considered as an effective means to increase mobility, reduce personal vehicle usage and related carbon emissions. In this paper, we consider problems of allocating a carshare fleet to service zones under uncertain one-way and round-trip rental demand. We employ a two-stage stochastic integer programming model, where in the first stage, we allocate shared vehicle fleet and purchase parking lots or permits in reservation-based or free-floating systems. In the second stage, we generate a finite set of samples to represent demand uncertainty and construct a spatial-temporal network for each sample to model vehicle movement and the corresponding rental revenue, operating cost, and penalties from unserved demand. We minimize the expected total costs minus profit, and develop branch-and-cut algorithms with mixed-integer rounding-enhanced Benders cuts, which can significantly improve computation efficiency when implemented in parallel computing. We apply our model to a data set of Zipcar in the Boston-Cambridge area to demonstrate the efficacy of our approaches and draw insights on carshare management. Our results show that exogenously given one-way demand can increase carshare profitability under given one-way and round-trip price difference and vehicle relocation cost, whereas endogenously generated one-way demand as a result of pricing and strategic customer behavior may decrease carshare profitability. Our model can also be applied in a rolling-horizon framework to deliver optimized vehicle relocation decisions and achieve significant improvement over an intuitive fleet-rebalancing policy.

Keywords: carshare, demand uncertainty, quality-of-service (QoS), two-stage stochastic integer programming, Benders decomposition, mixed-integer rounding

Suggested Citation

Lu, Mengshi and Chen, Zhihao and Shen, Siqian, Optimizing the Profitability and Quality of Service in Carshare Systems Under Demand Uncertainty (March 30, 2017). Available at SSRN: https://ssrn.com/abstract=2992951 or http://dx.doi.org/10.2139/ssrn.2992951

Mengshi Lu

Purdue University - Krannert School of Management ( email )

403 W State Street
West Lafayette, IN 47907
United States

Zhihao Chen

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Siqian Shen (Contact Author)

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

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