UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles

Velazquez Abad, AVA; Cherrett, TJ; Waterson, B; (2016) Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles. International Journal of Logistics Research and Applications 10.1080/13675567.2016.1203395. (In press). Green open access

[thumbnail of Velazquez_Abad_Sim-Heuristics_Low_Carbon.pdf]
Preview
Text
Velazquez_Abad_Sim-Heuristics_Low_Carbon.pdf - Accepted Version

Download (637kB) | Preview

Abstract

UK logistics fleets face increasing competitive pressures due to volatile fuel prices and the small profit margins in the industry. By reducing fuel consumption, operational costs and carbon emissions can be reduced. While there are a number of technologies that can reduce fuel consumption, it is often difficult for logistics companies to identify which would be the most beneficial to adopt over the medium and long terms. With a myriad of possible technology combinations, optimising the vehicle specification for specific duty cycles requires a robust decision-making framework. This paper combines simulated truck and delivery routes with a metaheuristic evolutionary algorithm to select the optimal combination of low-carbon technologies that minimise the greenhouse gas emissions of long-haul heavy goods vehicles during their lifetime cost. The framework presented is applicable to other vehicles, including road haulage, waste collection fleets and buses by using tailored parameters in the heuristics model.

Type: Article
Title: Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles
Open access status: An open access version is available from UCL Discovery
DOI: 10.1080/13675567.2016.1203395
Publisher version: http://dx.doi.org/10.1080/13675567.2016.1203395
Language: English
Additional information: Copyright © 2016 Informa UK Limited, trading as Taylor & Francis Group. This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Logistics Research and Applications on 18 July 2016, available online: http://dx.doi.org/10.1080/13675567.2016.1203395
Keywords: Sim-heuristics, freight, heavy goods vehicles, energy, GHG, technology
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources
URI: https://discovery.ucl.ac.uk/id/eprint/1504516
Downloads since deposit
110Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item