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

Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles
Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles
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.
Sim-heuristics, freight, heavy goods vehicles, energy, GHG, technology
1367-5567
3-19
Velazquez, Anthony
c8cb6104-4c01-4efc-8203-b25df93d476e
Cherrett, Thomas
e5929951-e97c-4720-96a8-3e586f2d5f95
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286
Velazquez, Anthony
c8cb6104-4c01-4efc-8203-b25df93d476e
Cherrett, Thomas
e5929951-e97c-4720-96a8-3e586f2d5f95
Waterson, Ben
60a59616-54f7-4c31-920d-975583953286

Velazquez, Anthony, Cherrett, Thomas and Waterson, Ben (2017) Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles. International Journal of Logistics Research and Applications, 20 (1), 3-19. (doi:10.1080/13675567.2016.1203395).

Record type: Article

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.

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Accepted/In Press date: 14 June 2016
e-pub ahead of print date: 18 July 2016
Published date: January 2017
Keywords: Sim-heuristics, freight, heavy goods vehicles, energy, GHG, technology
Organisations: Transportation Group

Identifiers

Local EPrints ID: 398366
URI: http://eprints.soton.ac.uk/id/eprint/398366
ISSN: 1367-5567
PURE UUID: 25c4e6ec-9502-4b29-b03b-b6fec06578ec
ORCID for Ben Waterson: ORCID iD orcid.org/0000-0001-9817-7119

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Date deposited: 25 Jul 2016 09:32
Last modified: 07 Oct 2020 04:55

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Contributors

Author: Anthony Velazquez
Author: Thomas Cherrett
Author: Ben Waterson ORCID iD

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