title: Modified genetic algorithm for parameter selection of compartmental models.
abstract: A Modified Genetic Algorithm has been developed for the task of optimal parameter selection for compartmental models. As a case study, a predictive model of the emerging health threat of obesity in America was developed which incorporated varying levels of three treatment strategies in an attempt to decrease the amount of overweight Americans over a ten-year period. The Genetic Algorithm was then applied to the task of minimizing the number of overweight persons while minimizing the costs associated with implementing the chosen treatment plans. Throughout repeated trials, the GA was able to converge to consistent, high-scoring treatment strategies after only a few minutes of computation on a desktop PC. This result demonstrates the ability of the modified Genetic Algorithm to effectively perform multivariate, nonlinear, simulation-based optimization routines in a short time.
authors.affiliation: Department of Biomedical Engineering, Georgia Institute of Technology, GA 30332 USA. neil.shah@gatech.edu
authors.forename: Neil A
authors.initials: NA
authors.lastname: Shah
authors.forename: Richard A
authors.initials: RA
authors.lastname: Moffitt
authors.forename: May D
authors.initials: MD
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D008019:Life Style; D008957:Models, Genetic; D009765:Obesity / Q000209:etiology / Q000235:genetics; D014481:United States