Optimal Design of Reinforced Concrete Retaining Walls using a Swarm Intelligence Technique

摘要

This paper concerns with the optimal design of reinforced concrete earth-retaining walls. In recent years, successful applications of Particle Swarm Optimization (PSO) in many optimization benchmark problems have been reported and indicated that PSO is a robust algorithm and is more efficient, requiring fewer number of function evaluations, while leading to better or the same quality of results. Here, we propose to use PSO to optimize walls. The optimal wall design problem is obviously a constrained optimization problem. To deal with the constraints a dynamic penalties approach is used. The formulation of the problem includes important design variables such as geometrical ones; describing thickness of the kerb and the footing, as well as the toe and the heel lengths and variables describing the reinforcement set-up. Results show the ability of the proposed methodology to find an optimal solution for economical design of retaining wall structures.