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Freight transport, routing software and time-dependent vehicle routing models

Freight transport, routing software and time-dependent vehicle routing models
Freight transport, routing software and time-dependent vehicle routing models
Routing and scheduling software is part of the Information and Technology systems available to support the transport industry, and uses complex algorithms along with geographical representations of the road network to allow better planning of daily collection and delivery schedules. This research reviews the evolution of routing and scheduling software, the algorithms used along with reported barriers to wider take-up and potential industry driven improvements that could be made. A survey of transport companies in the United Kingdom was conducted in order to validate and prioritize the software capabilities that require the most development according to the new challenges that the industry is facing. Responses suggested that companies required improved route optimization to tackle congestion based on time-dependent data and models, and greater accuracy in the representation of the road network. Not considering congestion leads to the underestimation of travel times and the production of inaccurate schedules. Literature shows that operational research techniques are available to solve problems that represent real world conditions, but research into the relative merits of using time-dependent models needs to be undertaken.

Although exact methods have been developed to solve the Vehicle Routing Problem, they cannot cope with large instances and rich variants that are required by the industry. Therefore, metaheuristic algorithms are usually implemented in routing software. A reported barrier in metaheuristic algorithms is the lack of accuracy (the difference between optimal or best-known values and the result of the proposed algorithm). In this research an algorithm was developed using elements of Large Neighbourhood Search that is capable to substantially improve the state of the art for the time-dependent Vehicle Routing Problem. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable time. A variant that considers the Rules on Drivers’ hours required in the scheduling of vehicles over 3.5 tons in the European Union and the UK is also introduced. Analysis of results show result improvements in number of vehicles (19.0%), travel distance (17.7%) and route duration (4.4%) compared to previous implementations.
Rincon Garcia, Nicolas
cc375b49-2591-4bb1-9bff-b9ded24fd934
Rincon Garcia, Nicolas
cc375b49-2591-4bb1-9bff-b9ded24fd934
Waterson, Benedict
60a59616-54f7-4c31-920d-975583953286

(2016) Freight transport, routing software and time-dependent vehicle routing models. University of Southampton, Faculty of Engineering and the Environment, Doctoral Thesis, 144pp.

Record type: Thesis (Doctoral)

Abstract

Routing and scheduling software is part of the Information and Technology systems available to support the transport industry, and uses complex algorithms along with geographical representations of the road network to allow better planning of daily collection and delivery schedules. This research reviews the evolution of routing and scheduling software, the algorithms used along with reported barriers to wider take-up and potential industry driven improvements that could be made. A survey of transport companies in the United Kingdom was conducted in order to validate and prioritize the software capabilities that require the most development according to the new challenges that the industry is facing. Responses suggested that companies required improved route optimization to tackle congestion based on time-dependent data and models, and greater accuracy in the representation of the road network. Not considering congestion leads to the underestimation of travel times and the production of inaccurate schedules. Literature shows that operational research techniques are available to solve problems that represent real world conditions, but research into the relative merits of using time-dependent models needs to be undertaken.

Although exact methods have been developed to solve the Vehicle Routing Problem, they cannot cope with large instances and rich variants that are required by the industry. Therefore, metaheuristic algorithms are usually implemented in routing software. A reported barrier in metaheuristic algorithms is the lack of accuracy (the difference between optimal or best-known values and the result of the proposed algorithm). In this research an algorithm was developed using elements of Large Neighbourhood Search that is capable to substantially improve the state of the art for the time-dependent Vehicle Routing Problem. Comparison of results with available test instances shows that the proposed algorithm is capable of obtaining a reduction in the number of vehicles (4.15%), travel distance (10.88%) and travel time (12.00%) compared to previous implementations in reasonable time. A variant that considers the Rules on Drivers’ hours required in the scheduling of vehicles over 3.5 tons in the European Union and the UK is also introduced. Analysis of results show result improvements in number of vehicles (19.0%), travel distance (17.7%) and route duration (4.4%) compared to previous implementations.

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More information

Published date: 1 June 2016
Organisations: University of Southampton, Transportation Group

Identifiers

Local EPrints ID: 397141
URI: http://eprints.soton.ac.uk/id/eprint/397141
PURE UUID: 96e481ae-0695-470c-82d2-f0d526ff31dc
ORCID for Benedict Waterson: ORCID iD orcid.org/0000-0001-9817-7119

Catalogue record

Date deposited: 12 Jul 2016 15:22
Last modified: 20 Jun 2018 00:34

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Contributors

Author: Nicolas Rincon Garcia
Thesis advisor: Benedict Waterson ORCID iD

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