State of the Art on the Use of Genetic Algorithms in Design of Steel Structures

INTRODUCTION During the last three decades, many mathematical programming methods have been developed for solving optimization problems (Gallagher and Zienkiewicz, 1973; Hillier and Lieberman, 1990). However, no single method has been found to be entirely efficient and robust for the wide range of engineering optimization problems (Rajeev and Krishnamoorthy, 1992). Most design applications in civil engineering involve selecting values for a set of design variables that best describe the behavior and performance of the particular problem while satisfying the requirements and specifications imposed by codes of practice. Mathematically these design variables are discrete for most practical design problems. However, most mathematical optimization applications are suited and developed for continuous design variables. In discrete optimization problems, searching for the global or a local optimal solution becomes a difficult task. A few mathematical methods have been developed for solving problems in discrete optimization. These methods include complete enumeration techniques, integer programming, branch and bound algorithms, and dynamic programming. All these methods use mathematical programming techniques.