Effectiveness of demand and fulfillment control in dynamic fleet management of ride‐sharing systems. Issue 3 (4th June 2021)

• Record Type: Journal Article
• Authors: Haferkamp, Jarmo; Ehmke, Jan Fabian
• Is Part Of: Networks. Volume 79:Issue 3(2022)
• Page Start: 314
• Page End: 337
• Publication Date: 2021-06-04
• Subjects: anticipation -- dial‐a‐ride problem -- dynamic vehicle routing -- large neighborhood search -- ride‐sharing -- stochastic requests; Network analysis (Planning) -- Periodicals; 658.4032
• DOI: 10.1002/net.22062
• Languages: English
• ISSNs: 0028-3045

Abstract

Abstract: In recent years, innovative ride‐sharing systems have gained significant attention. In such systems, dynamic fleet management covers demand and fulfillment control to determine which stochastically incoming requests are to be satisfied and how vehicle resources are utilized for their fulfillment, respectively. Demand and fulfillment control can be implemented ranging from straightforward myopic to more sophisticated anticipatory. In this paper, our aim is twofold: (1) we want to classify how policies implement demand and fulfillment control in the related literature on dynamic fleet management; (2) we want to explore the effectiveness of demand and fulfillment control under varying conditions in order to identify benefits and risks for ride‐sharing systems. To this end, we define policies that differ in the optimization of demand and/or fulfillment control through the exploitation of either confirmed or complete information. Our experimental results demonstrate that demand and fulfillment control affect the performance and service quality of ride‐sharing systems quite differently.