Recent developments in optimization techniques that deal with finding the solution of combinatorial optimization problems has provided steel designers with new capabilities. These new optimization techniques use nature as a source of inspiration to develop new procedures for solving complex engineering problems. Among these, evolutionary algorithms mimic evolutionary biology and make use of the principle of the survival of the fittest to establish a numerical search algorithm. In the immune system algorithm a population of antibodies is evolved to cover a set of antigens as is the case in the vertebrate immune system. Simulated annealing imitates the cooling process of molten metals through annealing. Swarm intelligence is based on the collective behaviour of bird flocking or fish schooling. Ant colony optimization method simulates the social interaction of ant colonies. It has been discovered that ants, while being completely blind, can successfully commute between their nest and food sources by following the shortest path. Ant colony optimization mimics this behaviour of the real ant colony to achieve difficult computations. The harmony search method is based on the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. It became possible through use of these novel techniques to develop structural optimization methods that find the optimum steel sections required for the frame members from the discrete available section lists such that design constraints imposed by design codes are satisfied while the cost or weight of the frame is minimized. This paper firstly introduces the formulation of the steel frame optimization problem where the constraints are implemented from steel design codes. It then reviews the recent structural optimization algorithms that are based on naturally inspired computing methods.