A Road Timetable to aid vehicle routing and scheduling

Eglese, Richard W.; Maden, Will; Slater, Alan

doi:10.1016/j.cor.2005.03.029

Cited by 84 publications

(71 citation statements)

References 8 publications

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“…These ideas have been treated in Haghani and Jung (2005) and Chen et al (2005). More recently, Eglese et al (2006) discussed the issues involved in order to construct a database of road times for a road network. More details are developed in Maden (2006).…”

Section: Time-dependent Vehicle Routingmentioning

confidence: 99%

Combinatorial optimization and Green Logistics

Sbihi¹,

Eglese²

2009

Ann Oper Res

232

106

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Section: Time-dependent Vehicle Routingmentioning

confidence: 99%

Combinatorial optimization and Green Logistics

Sbihi¹,

Eglese²

2009

Ann Oper Res

232

106

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“…Eglese et al [7] show how the use of time-dependent data can affect results for a hypothetical distribution operation and develop a model to use the historical data to construct a Road Timetable that shows the shortest time between nodes when the journeys start at different times. The shortest times and routes may vary as the speed of travel on individual roads may differ significantly by the hour of the day, by the day of the week and by the season of the year.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The LANTIME algorithm works on one set of Road Timetables which are described in Eglese et al [7]. The LANCOST algorithm works on two sets of Cost Based Road Timetables.…”

Section: Differences Between Lantime and Lancostmentioning

confidence: 99%

Minimum cost VRP with time-dependent speed data and congestion charge

Wen

Eglese

2015

Computers & Operations Research

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A heuristic algorithm, called LANCOST, is introduced for vehicle routing and scheduling problems to minimize the total travel cost, where the total travel cost includes fuel cost, driver cost and congestion charge. The fuel cost required is influenced by the speed. The speed for a vehicle to travel along any road in the network varies according to the time of travel. The variation in speed is caused by congestion which is greatest during morning and evening rush hours. If a vehicle enters the congestion charge zone at any time, a fixed charge is applied. A benchmark dataset is designed to test the algorithm. The algorithm is also used to schedule a fleet of delivery vehicles operating in the London area.

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“…Weather conditions and 'random' effects caused by accidents, broken-down vehicles and so on also have an impact. Nevertheless, route planners can benefit from historical data for traffic volume and road speed, to help them avoid using certain roads at regularly congested times (Eglese et al, 2006).…”

Section: Time-varying Travel Networkmentioning

confidence: 99%

Investigating the use of metaheuristics for solving single vehicle routing problems with time-varying traversal costs

Harwood

Mumford

Eglese

2013

Journal of the Operational Research Society

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Metaheuristic algorithms, such as simulated annealing and tabu search, are popular solution techniques for vehicle routing problems (VRPs). These approaches rely on iterative improvements to a starting solution, involving slight alterations to the routes (ie, neighbourhood moves), moving a node to a different part of a solution, swapping nodes or inverting sections of a tour, for example. When working with standard VRPs, where the costs of the arcs do not vary with advancing time, evaluating changes to the total cost following a neighbourhood move is a simple process: simply subtract the cost of the links removed from the solution and add the costs for the new links. When a time-varying aspect (eg, congestion) is included in the costs, these calculations become estimations rather than exact values. This paper focuses on a single vehicle routing problem, similar to the Travelling Salesman Problem, and investigates the potential for using estimation methods on simple models with time-variant costs, mimicking the effects of road congestion.

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A Road Timetable to aid vehicle routing and scheduling

Cited by 84 publications

References 8 publications

Combinatorial optimization and Green Logistics

Combinatorial optimization and Green Logistics

Minimum cost VRP with time-dependent speed data and congestion charge

Investigating the use of metaheuristics for solving single vehicle routing problems with time-varying traversal costs

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