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.

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

cost optimization , structural optimum design , particle swarm optimization algorithm , multi-criterion decision-making , reinforced concrete structures.