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Green Logistics : Advanced Methods for Transport Logistics Management Systems Including Platooning and Alternative Fuel Powered Vehicles

Furneaux, Angus (2021) Green Logistics : Advanced Methods for Transport Logistics Management Systems Including Platooning and Alternative Fuel Powered Vehicles. Doctor of Philosophy (PhD) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.89043) (KAR id:89043)

Abstract

Green Logistics has attracted increased attention from researchers during the last few years, due to the growing environmental awareness. Road Transport is a major factor in climate change and accounts for a large proportion of the total UK emissions, including Carbon Dioxide (CO₂). With traffic and congestion levels growing, efficient routing combined with greener (more environmentally friendly) vehicles will be of great importance. The purpose of this thesis is two-fold: i) to provide an insight into Green Logistics and ways in which green technologies can be combined within the vehicle routing problem and ii) identifying new variants of the Vehicle Routing Problem (VRP) that can be applied to real-life instances; The Platooning Routing Problem with Changing Split Points, and the proposition of a Hyper-Realistic Electric Vehicle Energy Consumption model that can be applied to the E-VRP. A thorough CO₂ experiment was also conducted on a rolling road, providing useful data that future research can use to further increase the accuracy of routing models. The platooning of vehicles proves to be an important technique that can lead to large decreases in fuel consumption and can be easily implemented in most transport systems; the process requires advanced and accurate computer systems that are only now becoming available to manufacturers. The Platooning model is designed and tested within this thesis and it is hoped to spark further interest in this crucial area of research. Extensions to the Platooning Problem include the addition of heterogeneous fleets and how they change the dynamics of the proposed problems, as well as further work on the placement of the critical splitting point. Allowing the consideration of using limited range Electric Vehicles (EVs) as well as Conventional Vehicles (CVs) and Alternative Fuel powered Vehicles (AFVs) can further increase the emission savings and are becoming progressively popular in today's society. We therefore have carried out extensive research around the area of AFV's including detailed battery specifics for EV's. The objective is to minimise the amount of emissions while satisfying the time window requirements of customers maintaining low overall financial costs. The resulting emissions are largely affected by the electricity fuel mix of the country, we found that the indirect EV emissions for a 30kwh EV can vary by as much as 33% throughout the day and as much as 68% throughout the year with different seasons. Various heuristic and metaheuristic solution techniques as well as several classical heuristics are implemented including the Clarke and Wright Savings heuristic algorithm (CWSA), the Sweep Algorithm and the Variable Neighbourhood Search (VNS) method. These heuristic and metaheuristic models are tested on the Christofides et al. datasets and we achieve solutions that are on average 1.67% and 8.5% deviated from the best-known solution for unrestricted route lengths and restricted max route length problems respectively. Following this a platooning model is generated and tested on various datasets, including a real-life example along the roads of the South East of the UK. Platooning proves to bring benefits to the VRP, with the extensions discussed in this thesis providing increased savings to emissions. On three of the dataset problems of the small and medium size problems a significant fuel saving of more than 1% was achieved. With future research and additional avenues explored Platooning can make a significant reduction to emissions and make an impact on improving air quality. The EV model proposed is designed to trigger further research on ultra-realistic energy models with the aim of being applied to a real-life organisation with various constraints including factors such as battery health, travel speed, vehicle load and transportation distance. This thesis provides useful insights into how important the aspect of environmental route planning is, providing advice on tangible and intangible benefits such as cost savings and a reduction in carbon emissions.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Wassan, Niaz
Thesis advisor: Salhi, Said
Thesis advisor: O'Hanley, Jesse
DOI/Identification number: 10.22024/UniKent/01.02.89043
Uncontrolled keywords: Management Science, vehicle routing, platooning, green logistics, electric vehicles
Subjects: H Social Sciences > HE Transportation and Communications
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 08 Jul 2021 09:23 UTC
Last Modified: 05 Nov 2024 12:55 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/89043 (The current URI for this page, for reference purposes)

University of Kent Author Information

Furneaux, Angus.

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