期刊
COMPUTERS & INDUSTRIAL ENGINEERING
卷 162, 期 -, 页码 -出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cie.2021.107703
关键词
Carsharing; Heterogeneous fleet; Substitution; Stochastic programming; Sample average approximation; Integer programming
资金
- Strategic Basic Research project 'Datadriven logistics' - Research Foundation Flanders (FWO) [S007318N]
Carsharing has become a viable and cost-effective mode of transportation that helps improve the environment and reduce traffic congestion. System operators face the challenge of designing an efficient system that meets user demand while controlling operational costs. Vehicle substitution in carsharing systems can increase user experience but also impact expected profit.
Carsharing has become a viable alternative mode of transportation which not only contributes to a better environment and less traffic congestion, but is often also cheaper for its users. It is a challenging task for carsharing system operators to design an efficient system which meets user demand while at the same time limiting operational expenses. This problem becomes even more difficult if the provider offers a fleet of heterogeneous vehicles to users as this introduces the opportunity to substitute vehicle types. Substitution occurs when the requested vehicle type is not available and the user is instead assigned to a different, typically larger, vehicle. This paper investigates the main drivers of vehicle substitution in a round-trip carsharing system and how it affects profit. To account for uncertainty of demand, a two-stage stochastic programming model is proposed in which variables associated with user requests are considered random. A sample average approximation approach is used to find solutions within acceptable computation time. A computational study shows that the proposed method is able to closely approximate the true expected profit. Sensitivity analysis of different problem parameters demonstrates how the number of vehicles in use and the users' spatial flexibility increase the number of substitutions. A detailed analysis of solutions shows how vehicle substitution always positively impacts the expected profit.
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