Genetic search - An approach to the nonconvex optimization problem

Abstract

Principles of genetics and natural selection are adapted into a search procedure for function optimization. Such methods are based on a randomized selection from that restricted region of the design space that yields and improvement in the objective function. An implementation of the approach to a class of problems in structural optimization with demonstrated nonconvexities or disjointness is discussed in the paper. The principal drawback of the method is an increase in function evaluations necessary to locate an optimum. Possible strategies to overcome this limitation are presented