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Column Generation Method for U.S. Army Logistics Air Fleet Scheduling Li, Yihua ; Wang, Bruce X

By: Contributor(s): Series: Transportation Research Record: Journal of the Transportation Research Board ; 2197Publication details: Washington DC Transportation Research Board, 2010Description: s. 36-42ISBN:
  • 9780309160735
Subject(s): Bibl.nr: VTI P8167:2197Location: TRBAbstract: In a U.S. Army problem, an air fleet is scheduled to pick up and deliver military personnel with time window and aircraft capacity constraints. Demand for personnel flights between military bases has a number of unique features, such as priority demand and flexible delivery locations. A column generation method was adopted in which the resource-constrained shortest-path subproblem is solved as a schedule for a fleet vehicle. The master problem solves for an optimal set of schedules for the entire fleet. This column generation method is embedded in an automatic scheduling program (ASP) at the U.S. Joint Operational Support Airlift Center. A comparison of the ASP prototype and the current manual scheduling shows significant improvement potential to the operations for demand satisfaction and resource utilization.
Item type: Reports, conferences, monographs
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Statens väg- och transportforskningsinstitut Available

In a U.S. Army problem, an air fleet is scheduled to pick up and deliver military personnel with time window and aircraft capacity constraints. Demand for personnel flights between military bases has a number of unique features, such as priority demand and flexible delivery locations. A column generation method was adopted in which the resource-constrained shortest-path subproblem is solved as a schedule for a fleet vehicle. The master problem solves for an optimal set of schedules for the entire fleet. This column generation method is embedded in an automatic scheduling program (ASP) at the U.S. Joint Operational Support Airlift Center. A comparison of the ASP prototype and the current manual scheduling shows significant improvement potential to the operations for demand satisfaction and resource utilization.