Civil engineering applications of genetic algorithms

Abstract

Genetic Algorithms (GAs) are a class of computational models that mimic the process of natural evolution and adaptation to the environment. Many researchers have noted the parallel between the above and the `optimum' seeking behaviour required in many aspects of problem solving. There are an increasing number of hybridized applications that employ some form of evolutionary competition and adaptation in conjunction with the computer simulation of an engineering model. In this paper, we review three of these hybridized applications and share some of the insights gained from designing and operating hybridized GA applications.