Title :
Evolutionary programming
Author :
Cao, Y.J. ; Wu, Q.H.
Author_Institution :
Dept. of Electr. Eng. & Electron., Liverpool Univ., UK
Abstract :
This paper presents a mixed-variable evolutionary programming (MVEP) for solving mechanical design optimization problems which contain integer, discrete, zero-one and continuous variables. The MVEP provides an improvement in global search and convergence performance in a mixed-variable space. An approach to handle various kinds of variables and constraints is discussed. Two examples of mechanical design optimization are tested, which demonstrate that the proposed approach is superior to current methods for finding optimum solution, both in the quality of solution and convergence performance
Keywords :
CAD; convergence; genetic algorithms; mechanical engineering; mechanical engineering computing; problem solving; search problems; constraints; continuous variables; convergence performance; discrete variables; global search; integer variables; mechanical design optimization; mixed-variable evolutionary programming; problem solving; quality; zero-one variables; Constraint optimization; Design optimization; Gears; Genetic programming; Linear programming; Matrix converters; Quadratic programming; Symmetric matrices; Teeth; Testing;
Conference_Titel :
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
0-7803-3949-5
DOI :
10.1109/ICEC.1997.592352
