Matching Functions for Free-Floating Shared Mobility System Optimization to Capture Maximum Walking Distances

European Journal of Operational Research - DOI: https://doi.org/10.1016/j.ejor.2022.06.058

49 Pages Posted: 28 Jul 2021 Last revised: 6 Jul 2022

See all articles by Matthias Soppert

Matthias Soppert

Bundeswehr University Munich

Claudius Steinhardt

Bundeswehr University Munich

Christian Müller

University of Duisburg-Essen - Mercator School of Management

Jochen Gönsch

University of Duisburg-Essen - Mercator School of Management

Prasanna Bhogale

SHARE NOW

Date Written: July 4, 2022

Abstract

Shared mobility systems have become a frequently used inner-city mobility option. In particular, free-floating shared mobility systems are experiencing strong growth compared to station-based systems. For both, many approaches have been proposed to optimize operations, e.g., through pricing and vehicle relocation. To date, however, optimization models for free-floating shared mobility systems have simply adopted key assumptions from station-based models. This refers, in particular, to the models' part that formalizes how rentals realize depending on available vehicles and arriving customers, i.e., how supply and demand match. However, this adoption results in simplifications that do not adequately account for the unique characteristics of free-floating systems, leading to overestimated rentals, suboptimal decisions, and lost profits.

In this paper, we address the issue of accurate optimization model formulation for free-floating systems. Thereby, we build on the state-of-the-art concept of considering a spatial discretization of the operating area into zones. We formally derive two novel analytical matching functions specifically suited for free-floating system optimization, incorporating additional parameters besides supply and demand, such as customers' maximum walking distance and zone sizes. We investigate their properties, like their linearizability and integrability into existing optimization models. Our computational study shows that the two functions’ accuracy can be up to 20 times higher than the existing approach. In addition, in a pricing case study based on data of Share Now, Europe’s largest free-floating car sharing provider, we demonstrate that more profitable pricing decisions are made. Most importantly, our work enables the adaptation of station-based optimization models to free-floating systems.

Keywords: Transportation, Free-Floating Shared Mobility Systems, Modeling, Matching Functions, Optimization

JEL Classification: C44, M19

Suggested Citation

Soppert, Matthias and Steinhardt, Claudius and Müller, Christian and Gönsch, Jochen and Bhogale, Prasanna, Matching Functions for Free-Floating Shared Mobility System Optimization to Capture Maximum Walking Distances (July 4, 2022). European Journal of Operational Research - DOI: https://doi.org/10.1016/j.ejor.2022.06.058, Available at SSRN: https://ssrn.com/abstract=3881718 or http://dx.doi.org/10.2139/ssrn.3881718

Matthias Soppert (Contact Author)

Bundeswehr University Munich ( email )

Werner-Heisenberg-Weg 39
Neubiberg, 85577
Germany

Claudius Steinhardt

Bundeswehr University Munich ( email )

Werner-Heisenberg-Weg 39
Neubiberg, 85577
Germany

HOME PAGE: http://www.unibw.de/quantitative-methoden

Christian Müller

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany

Jochen Gönsch

University of Duisburg-Essen - Mercator School of Management ( email )

Lotharstraße 65
Duisburg, Nordrhein-Westfalen 47057
Germany
+49 203 379 - 2777 (Phone)
+49 203 379 - 1760 (Fax)

HOME PAGE: http://udue.de/goensch

Prasanna Bhogale

SHARE NOW ( email )

Kaufhaus Jahndorf
Brunnenstr. 19-21
Berlin, 10119
Germany

HOME PAGE: http://https://www.share-now.com/de/en/

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