Title :
Optimizing complex systems
Author :
Haupt, Sue Ellen ; Haupt, Randy L.
Author_Institution :
Dept. of Mech. Eng., Nevada Univ., Reno, NV, USA
Abstract :
Modeling and solving complex engineering problems requires new algorithmic tools. A promising new tool for numerical optimization is the genetic algorithm. This paper presents two interesting applications using the genetic algorithm. The first optimizes a function that has a subjective output: music. The second uses continuous parameters rather than the traditional binary parameters to find solutions to a nonlinear partial differential equation. A brief introduction to the continuous parameter genetic algorithm is given
Keywords :
genetic algorithms; nonlinear differential equations; partial differential equations; algorithmic tools; complex engineering problems; continuous parameter algorithm; continuous parameters; genetic algorithm; nonlinear partial differential equation; numerical optimization; subjective output; Biological cells; Concurrent computing; Cost function; Genetic algorithms; Mechanical engineering; Nonlinear equations; Optimization methods; Partial differential equations; Power system modeling; Sampling methods;
Conference_Titel :
Aerospace Conference, 1998 IEEE
Conference_Location :
Snowmass at Aspen, CO
Print_ISBN :
0-7803-4311-5
DOI :
10.1109/AERO.1998.682196
