A genetic algorithm for design of moment-resisting steel frames

This paper presents computational approaches that can be implemented in a decision support system for the design of moment-resisting steel frames. Trade-off studies are performed using genetic algorithms to evaluate the savings due to the inclusion of the cost of connections in the optimization model. Since the labor costs and material costs vary according to the geographical location and time of construction, the trade-off curves are computed for several values of the ratio between the cost of rigid connection and the cost of steel. A real-life 5-bay 5-story frame is used for illustration. Results indicate that the total cost of the frame is minimal when rigid connections are present only at certain locations. Finally, “Modeling to Generate Alternatives—MGA,” is proposed to generate good design alternatives as the solution from optimization may not be optimal with respect to the unmodeled objectives and constraints. It provides a set of alternatives that are near-optimal with respect to the modelled objectives and that are also farther from each other in the decision space. Results show that a final design could be chosen from the set of alternatives or obtained by tinkering one of the alternatives.