Wang, G, Xu, M, Grant-Muller, S et al. (1 more author) (2020) Combination of tradable credit scheme and link capacity improvement to balance economic growth and environmental management in sustainable-oriented transport development: A bi-objective bi-level programming approach. Transportation Research Part A: Policy and Practice, 137. pp. 459-471. ISSN 0965-8564
Abstract
In this paper, we propose a bi-objective bi-level programming model to balance economic growth and environmental management, which orients sustainable transport development by combining a tradable credit scheme (TCS) and a link capacity improvement measure. At the upper level, the decision maker aims to both maximize the economic benefit and minimize the total amount of traffic emissions by the optimal determination of a TCS and a link capacity improvement measure. The lower level is the user equilibrium problem, with elastic origin-destination (O-D) demand given the TCS and link capacity expansion measure. Further, a relaxation algorithm with a series of transformations is proposed to solve the proposed model. Numerical experiments illustrate the effectiveness of the proposed bi-objective bi-level model as well as the proposed relaxation algorithm. This study demonstrates how economic and environmental goals are influenced by the implementation of different development patterns comprising TCSs and link capacity improvements.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Keywords: | Sustainable transport system; Network design problem; Tradable credit scheme; Bi-objective bi-level programming model |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > Institute for Transport Studies (Leeds) > ITS: Sustainable Transport Policy (Leeds) |
Funding Information: | Funder Grant number ESRC (Economic and Social Research Council) ES/P01139X/1 ESRC (Economic and Social Research Council) ES/S007164/1 Alan Turing Institute No External Reference |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 Mar 2020 10:49 |
Last Modified: | 03 Sep 2020 14:37 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.tra.2018.10.031 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:158123 |