Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic algorithms for agent-based infrastructure interdependency modeling and analysis
SpringSim '07 Proceedings of the 2007 spring simulation multiconference - Volume 2
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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.