A mixed integer programming formulation and effective cuts for minimising schedule durations of Australian truck drivers

Transport companies seek to maximise vehicle utilisation and minimise labour costs. Both goals can be achieved if the time required to fulfil a sequence of transportation tasks is minimised. However, if schedule durations are too short drivers may not have enough time for recuperation and road safet...

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Veröffentlicht in:Journal of scheduling Jg. 15; H. 6; S. 733 - 741
1. Verfasser: Goel, Asvin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.12.2012
Springer Science + Business Media
Springer Nature B.V
Schlagworte:
Accreditation
Artificial Intelligence
Business and Management
Calculus of Variations and Optimal Control; Optimization
Driver fatigue
Drivers
Dynamic programming
Experiments
Fatigue
Heavy vehicles
Heuristic
Integer programming
Mixed integer
Operations Research/Decision Theory
Optimization
Programming
Regulation
Schedules
Scheduling
Studies
Supply Chain Management
Supply chains
Transport
Truck drivers
Trucks
Working hours
Australia
Multiple time windows
Vehicle scheduling
Australian Heavy Vehicle Driver Fatigue Law
Truck driver scheduling
ISSN:1094-6136, 1099-1425
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Zusammenfassung:Transport companies seek to maximise vehicle utilisation and minimise labour costs. Both goals can be achieved if the time required to fulfil a sequence of transportation tasks is minimised. However, if schedule durations are too short drivers may not have enough time for recuperation and road safety is impaired. In Australia transport companies must ensure that truck drivers can comply with Australian Heavy Vehicle Driver Fatigue Law and schedules must give enough time for drivers to take the amount of rest required by the regulation. This paper shows how transport companies can minimise the duration of truck driver schedules complying with Australian Heavy Vehicle Driver Fatigue Law. A mixed integer programming formulation is presented and valid inequalities are given. Computational experiments show that these inequalities provide significant reduction in computational effort when using one of the most advanced commercial mixed integer programming solver.
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ISSN:1094-6136
1099-1425
DOI:10.1007/s10951-012-0282-0