Optimization of simulation models with GADELO: a multi-population genetic algorithm.

M Elketroussi; D P Fan

doi:10.1016/0020-7101(94)90049-3

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Optimization of simulation models with GADELO: a multi-population genetic algorithm.

M Elketroussi·D P Fan

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Abstract

In this paper, a new Genetic Algorithm based on the Dynamic Exploration of Local Optima (GADELO) was used to estimate the parameters of the MRD (Micro-population model of Risk-group Dynamics) micro-population model for smoking cessation by minimizing a deviation function between the model's predictions and the smoking cessation data of the Multiple Risk Factor Intervention Trial (MRFIT). The efficiency and accuracy of the GADELO estimations were consistently superior to those obtained using the standard genetic algorithm or the simplex algorithm of Nelder-Mead.

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Algorithms Chromosomes Computer Simulation Crossing Over, Genetic Genetic Variation Genetics, Population Humans Models, Genetic Mutation Phenotype Population Dynamics Probability Risk Factors Selection, Genetic Smoking Smoking Cessation Smoking Prevention Stochastic Processes Journal Article

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M Elketroussi, D P Fan. 1994. Optimization of simulation models with GADELO: a multi-population genetic algorithm.. https://doi.org/10.1016/0020-7101(94)90049-3

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