Rapid Solutions to Hard Problems Using Fast Messy Genetic Algorithms

Abstract : This project developed and applied a type of non-traditional genetic algorithm called a fast messy genetic algorithm (fmGA). Critical bounding theory and computational experiments show that fmGAs converge to high quality solutions with high probability in times that grow no faster than a sub quadratic function of the number of decision variables. These results have important ramifications for the design and operation of the next generation of Air Force systems.