The University of Southampton
University of Southampton Institutional Repository

Enhancing carsharing pricing and operations through integrated choice models

Enhancing carsharing pricing and operations through integrated choice models
Enhancing carsharing pricing and operations through integrated choice models
Balancing supply and demand in free-floating one-way carsharing systems is a critical operational challenge. This paper presents a novel approach that integrates a binary logit model into a mixed integer linear programming framework to optimize short-term pricing and fleet relocation. Demand modeling, based on a binary logit model, aggregates different trips under a unified utility model and improves estimation by incorporating information from similar trips. To speed up the estimation process, a categorizing approach is used, where variables such as location and time are classified into a few categories based on shared attributes. This is particularly beneficial for trips with limited observations as information gained from similar trips can be used for these trips effectively. The modeling framework adopts a dynamic structure where the binary logit model estimates demand using accumulated observations from past iterations at each decision point. This continuous learning environment allows for dynamic improvement in estimation and decision-making. At the core of the framework is a mathematical program that prescribes optimal levels of promotion and relocation. The framework then includes simulated market responses to the decisions, allowing for real-time adjustments to effectively balance supply and demand. Computational experiments demonstrate the effectiveness of the proposed approach and highlight its potential for real-world applications. The continuous learning environment, combining demand modeling and operational decisions, opens avenues for future research in transportation systems.
Carsharing, Combinatorial optimization, Discrete choice models, Fleet relocation, Pricing
1366-5545
Oliveira, Beatriz Brito
bbd60075-a973-47a1-8b20-0d6c04277db4
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687
Oliveira, Beatriz Brito
bbd60075-a973-47a1-8b20-0d6c04277db4
Ahipasaoglu, Selin Damla
d69f1b80-5c05-4d50-82df-c13b87b02687

Oliveira, Beatriz Brito and Ahipasaoglu, Selin Damla (2025) Enhancing carsharing pricing and operations through integrated choice models. Transportation Research Part E: Logistics and Transportation Review, 195, [103993]. (doi:10.1016/j.tre.2025.103993).

Record type: Article

Abstract

Balancing supply and demand in free-floating one-way carsharing systems is a critical operational challenge. This paper presents a novel approach that integrates a binary logit model into a mixed integer linear programming framework to optimize short-term pricing and fleet relocation. Demand modeling, based on a binary logit model, aggregates different trips under a unified utility model and improves estimation by incorporating information from similar trips. To speed up the estimation process, a categorizing approach is used, where variables such as location and time are classified into a few categories based on shared attributes. This is particularly beneficial for trips with limited observations as information gained from similar trips can be used for these trips effectively. The modeling framework adopts a dynamic structure where the binary logit model estimates demand using accumulated observations from past iterations at each decision point. This continuous learning environment allows for dynamic improvement in estimation and decision-making. At the core of the framework is a mathematical program that prescribes optimal levels of promotion and relocation. The framework then includes simulated market responses to the decisions, allowing for real-time adjustments to effectively balance supply and demand. Computational experiments demonstrate the effectiveness of the proposed approach and highlight its potential for real-world applications. The continuous learning environment, combining demand modeling and operational decisions, opens avenues for future research in transportation systems.

Text
1-s2.0-S1366554525000341-main - Version of Record
Download (3MB)

More information

Accepted/In Press date: 21 January 2025
e-pub ahead of print date: 30 January 2025
Published date: 30 January 2025
Keywords: Carsharing, Combinatorial optimization, Discrete choice models, Fleet relocation, Pricing

Identifiers

Local EPrints ID: 498112
URI: http://eprints.soton.ac.uk/id/eprint/498112
ISSN: 1366-5545
PURE UUID: 6226da64-2669-45b5-934e-cf8edfe43c52
ORCID for Selin Damla Ahipasaoglu: ORCID iD orcid.org/0000-0003-1371-315X

Catalogue record

Date deposited: 10 Feb 2025 17:44
Last modified: 22 Aug 2025 02:29

Export record

Altmetrics

Contributors

Author: Beatriz Brito Oliveira

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×