Genetic Algorithm Optimisation of Mathematical Models Using Distributed Computing

Abstract

In this paper, a process by which experimental, or historical, data are used to create physically meaningful mathematical models is demonstrated. The procedure involves optimising the correlation between this ‘real world’ data and the mathematical models using a genetic algorithm which is constrained to operate within the physics of the system. This concept is demonstrated here by creating a structural dynamic finite element model for a complete F/A-18 aircraft based on experimental data collected by shaking the aircraft when it is on the ground. The processes used for this problem are easily broken up and solved on a large number of PCs. A technique is described here by which such distributed computing can be carried out using desktop PCs within the secure computing environment of the Defence Science & Technology Organisation without compromising PC or the network security.KeywordsGenetic AlgorithmSimplex AlgorithmGenetic Algorithm OptimisationTechnology OrganisationHome DirectoryThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.