Showing papers on "Quality control and genetic algorithms published in 1986"
••
01 Jan 1986TL;DR: GA's are shown to be effective for both levels of the systems optimization problem and are applied to the second level task of identifying efficient GA's for a set of numerical optimization problems.
Abstract: The task of optimizing a complex system presents at least two levels of problems for the system designer. First, a class of optimization algorithms must be chosen that is suitable for application to the system. Second, various parameters of the optimization algorithm need to be tuned for efficiency. A class of adaptive search procedures called genetic algorithms (GA) has been used to optimize a wide variety of complex systems. GA's are applied to the second level task of identifying efficient GA's for a set of numerical optimization problems. The results are validated on an image registration problem. GA's are shown to be effective for both levels of the systems optimization problem.
2,924 citations
•
TL;DR: In this article, the application of a GA to the optimal design of a ten member, plane truss is considered, and results show surprising speed as near-optimal results are obtained after examining a small fraction of the search space.
Abstract: The application of a genetic algorithm (GA) to the optimal design of a ten member, plane truss is considered. Genetic algorithms are search procedures based upon the mechanics of natural genetics, combining a Darwinian survival-of-the-fittest with a randomized, yet structured information exchange among a population of artificial chromosomes. Computer results show surprising speed as near-optimal results are obtained after examining a small fraction of the search space. The method is ready for application to more complex problems of engineering optimization.
309 citations