A COMBINATION OF PARTICLE SWARM OPTIMIZATION AND MULTI-CRITERION DECISION-MAKING FOR OPTIMUM DESIGN OF REINFORCED CONCRETE FRAMES

Structural design optimization usually deals with multiple conflicting objectives to obtain the minimum construction cost, minimum weight, and maximum safety of the final design. Therefore, finding the optimum design is hard and time-consuming for such problems. In this paper, we borrow the basic concept of multi-criterion decision-making and combine it with Particle Swarm Optimization (PSO) to develop an algorithm for accelerating convergence toward the optimum solution in structural multi-objective optimization scenarios. The effectiveness of the proposed algorithm was illustrated in some benchmark reinforced concrete (RC) optimization problems. The main goal was to minimize the cost or weight of structures while satisfying all design requirements imposed by design codes. The results confirm the ability of the proposed algorithm to efficiently find optimal solutions for structural optimization problems.