Optimal constrained design of steel structures by differential evolutionary algorithms

Structural optimization, when approached by conventional (gradient based) minimization algorithms presents several difficulties, mainly related to computational aspects for the huge number of nonlinear analyses required, that regard both Objective Functions (OFs) and Constraints. Moreover, from the early '80s to today's, Evolutionary Algorithms have been successfully developed and applied as a computational alternative to many optimization problems, such as structural ones. In this study the effectiveness of a relatively new Evolutionary Algorithm, namely Differential Evolutionary, is investigated for constrained optimization. This presents many interesting advantages and so that it is a candidate to be widely used in many real structural optimization problems. The algorithm version here used has been developed by hybridizing some recent versions of Differential Evolutionary algorithms proposed in literature, and uses a specific way for dealing with constraints which, always, concern real structural optimization problems. The effectiveness of proposed approach has been demonstrated by developing two cases of study, which regard simple but very significant structural problems for steel structures, one of which is a standard benchmark in structural optimization. The analyses show the simplicity and effectiveness of the proposed approach, so that it can be suitably ready for practical uses out of academic contest.