DocumentCode
1806529
Title
Modeling and Simulation of Canadian Forces Strategic Lift Strategies
Author
Ghanmi, Ahmed ; Shaw, R.H.A.D.
Author_Institution
Center for Oper. Res. & Anal., Defence Res. & Dev. Canada, Ottawa, Ont.
fYear
2006
fDate
3-6 Dec. 2006
Firstpage
1340
Lastpage
1348
Abstract
In support of Canadian forces (CF) transformation, a study was conducted to explore strategic lift movement strategies within the context of rapid deployability to counter asymmetric threats in failed or failing states around the globe. This study makes extensive use of two interconnected models. An aircraft loading optimization model using a combination of simulated annealing and genetic algorithm techniques with a novel convex hull based measure of effectiveness was developed to derive near-optimal loading plans across a fleet of transportation assets. The output from the loading model was then fed into a Monte Carlo simulation framework developed to allow for study of the effectiveness of a variety of strategic lift options. Analysis indicates that pre-positioning of equipment at various international locations and increased use of C-17 aircraft for airlift -where economically viable - could be potential strategies for improvement of the CF strategic lift
Keywords
Monte Carlo methods; genetic algorithms; military aircraft; simulated annealing; transportation; C-17 aircraft; Canadian forces strategic lift strategies; Monte Carlo simulation; aircraft loading optimization model; asymmetric threats; genetic algorithm; near-optimal loading plans; rapid deployability; simulated annealing; transportation assets; Air transportation; Analytical models; Context modeling; Failure analysis; Genetic algorithms; Load modeling; Mathematical model; Military aircraft; Sea measurements; Simulated annealing;
fLanguage
English
Publisher
ieee
Conference_Titel
Simulation Conference, 2006. WSC 06. Proceedings of the Winter
Conference_Location
Monterey, CA
Print_ISBN
1-4244-0500-9
Electronic_ISBN
1-4244-0501-7
Type
conf
DOI
10.1109/WSC.2006.323233
Filename
4117757
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