A GENETIC ALGORITHM FOR CONTINUOUS DESIGN SPACE SEARCH

Genetic algorithms (GAs) have been extensively used as a means for per forming global optimization in a simple yet reliable manner. However, in some realistic engineering design optimization domains the simple, classical implementation of a GA based on binary encoding and bit muta tion and crossover is often inefficient and unable to reach the global optimum. In this paper we describe a GA for continuous design space o ptimization that uses new GA operators and strategies tailored to the structure and properties of engineering design domains. Empirical resu lts in the domains of supersonic transport aircraft and supersonic mis sile inlets demonstrate that the newly formulated GA can be significan tly better than the classical GA in both efficiency and reliability. ( C) 1997 Elsevier Science Limited.