Abstract
This paper presents analysis of some of the strategic lift and pre-positioning issues within the context of rapid deployability to failed and failing states conducted for the Canadian Forces (CF). A simulation framework was developed to study the effectiveness of a variety of pre-positioning options. An aircraft loading optimization model based on a genetic annealing algorithm with a novel convex hull-based measure of effectiveness was also developed to analyse different strategic lift options. The model was used both to provide insights into the optimal mix of airlift capabilities and to conduct sensitivity analysis. Historical CF deployments provided a baseline performance measure against which several movement solutions were compared and contrasted. Analysis indicates that pre-positioning of equipment and supplies at various strategic locations and use of efficient mix of transport aircraft could be potential strategies for improvement of the CF's strategic lift capability.
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References
Baker SF, Morton DP, Rosenthal RE and Williams LM (2002). Optimizing military airlift. Opns Res 50(4): 582–602.
Cho H, Oh S and Choi D (1998). A new population-oriented simulated annealing technique based on local temperature concept. Electron Lett 34: 312–316.
Davis R (1992). Military afloat prepositioning: War time use and issues for the future. Report GAO/NSIAD-93-39, Government Accounting Office.
Dowsland K (1993). Some experiments with simulated annealing techniques for packing problems. Eur J Opl Res 68: 389–399.
Fund for Peace (2005). Failed states index 2005. Foreign Policy 149, (July/August): 56–65.
Ghanmi A, Haque L, Kaluzny BL and Shaw RHAD (2008). GALAHAD: Genetic Annealing for Loading of Aircraft, a Heuristic Aiding Deployment. Technical report, Defence Research and Development Canada—Centre for Operational Research and Analysis (forthcoming)..
Granger J, Krishnamurthy A and Robinson SM (2001). Stochastic modeling of airlift operations. In: Proceedings of the 2001 Winter Simulation Conference. Monterey, California.
Guéret C, Jussien N, Lhomme O, Pavageau C and Prins C (2003). Loading aircraft for military operations. J Opl Res Soc 54: 458–465.
Hypher RP (1980). Military airlift dynamics for laymen. ATGOR Staff Note 8/80, Operational Research Division, Trenton, Ontario.
Jakobs S (1996). On genetic algorithms for the packing of polygons. Eur J Opl Res 88: 165–181.
Lodi A, Martello S and Monaci M (2002). Two-dimensional packing problems: A survey. Eur J Opl Res 141: 241–252.
Lodi A, Martello S and Vigo D (1999). Heuristic and metaheuristic approaches for a class of two-dimensional bin packing problems. INFORMS J Comput 11: 345–357.
Lodi A, Martello S and Vigo D (2004). TSpack: A unified tabu search code for multi-dimensional bin packing problems. Ann Opns Res 131: 203–213.
Ng KYK (1992). A multicriteria optimization approach to aircraft loading. Opns Res 40(6): 1200–1205.
Pakhira MK (2003). A hybrid genetic algorithm using probabilistic selection. J Instit Eng (India) 84: 23–30.
Peltz E, Halliday JM and Bower A (2003). Speed and power: toward an expeditionary Army. Monograph Report MR 1755, RAND.
Rappoport HK, Levy LS, Golden BL and Toussaint KJ (1992). A planning heuristic for military airlift. Interfaces 22(3): 73–87.
Szeto R and Cooper B (2005). The need for Canadian strategic lift. Studies in defence and foreign policy, The Fraser Institute.
Vick A, Orletsky D, Pirnie B and Jones S (2002). The Stryker Brigade combat team: rethinking strategic responsiveness and assessing deployment options. Monograph Report MR 1606, RAND.
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Ghanmi, A., Shaw, R. Modelling and analysis of Canadian Forces strategic lift and pre-positioning options. J Oper Res Soc 59, 1591–1602 (2008). https://doi.org/10.1057/palgrave.jors.2602526
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DOI: https://doi.org/10.1057/palgrave.jors.2602526