Genetic algorithms in optimization problems with discrete and integer design variables

The paper describes an implementation of genetic search methods in the optimal design of structural systems with a mix of continuous, integer and discrete design variables. Design variable representation schemes for such mixed variables are proposed and the performance of each is evaluated in the context of structural design problems. The approach is proposed as an alternative to the branch-and-bound techniques that are used in conjunction with nonlinear programming methods. The methodology is inherently equipped with a better chance of locating the global optimum than the conventional gradient based methods.