Raeesi, Ramin, O'Sullivan, Michael J. (2014) Eco-logistics: Environmental and economic implications of alternative fuel vehicle routing problem. International Journal of Business Performance and Supply Chain Modelling, 6 (3-4). pp. 276-297. ISSN 1758-9401. (doi:10.1504/IJBPSCM.2014.065271) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:78267)
The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
Official URL: http://dx.doi.org/10.1504/IJBPSCM.2014.065271 |
Abstract
Alternative fuel vehicle (AFV) fleet adoption is an attractive mitigative measure to reduce environmental externalities from transportation activities of logistics. However, adequate economic and environmental attractions should be in place to encourage organisations to invest in AFVs. This paper introduces the alternative fuel vehicle routing problem (AFVRP), which is proposed to assist companies with an AFV fleet through both reducing the consumption level and optimising the utilisation of the alternative fuel. Distinguishing two dominant categories of AFVs as dedicated AFVs and bi-fuel vehicles, another extension of the problem as bi-fuel vehicle routing problem (BFVRP) is also studied. Experiments were run and the results indicated that for urban logistics networks a reduction by up to 35 in CO2 emissions and by up to 16 in costs is possible by using an AFV fleet and the proposed methodology instead of gasoline vehicles and the conventional VRP with a simple distance minimisation objective. Copyright © 2014 Inderscience Enterprises Ltd.
Item Type: | Article |
---|---|
DOI/Identification number: | 10.1504/IJBPSCM.2014.065271 |
Additional information: | cited By 0 |
Uncontrolled keywords: | alternative fuel vehicle, AFV, bi-fuel vehicle, vehicle routing, fuel consumption, environmental externalities, compressed natural gas, logistics, CO2 emission |
Subjects: | H Social Sciences |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Tracey Pemble |
Date Deposited: | 05 Nov 2019 14:41 UTC |
Last Modified: | 05 Nov 2024 12:42 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/78267 (The current URI for this page, for reference purposes) |
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):