Optimum Design of Reinforced Concrete Cantilever Retaining Walls by Cuckoo Optimization Algorithm (COA)

This paper presents an economical optimization for cost and weight of reinforcement cantilever concrete retaining walls using Cuckoo Optimization Algorithm (COA). The proposed optimization algorithm is inspired from the life of a bird family called cuckoo. The capability of this algorithm is compared with other optimization methods available in the literature including ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), particle swarm optimization (PSO), accelerated particle swarm optimization (APSO), firefly algorithm (FA), and cuckoo search (CS). A computer program has been developed by using the COA method for optimizing retaining walls. Five types of retaining walls were considered and sensitivity analyses were performed to find out the role of important parameters such including stem height, surcharge, backfill slope, and backfill unit weight and friction angle. Also, Coulomb and Rankine methods are used to estimate lateral earth pressures. The results show that the COA can minimize retaining walls from both cost and weight viewpoints. In addition, the COA can achieve to better results than ACO, BFOA, PSO, APSO, FA, and CS. The performed sensitivity analysis illustrates that with increasing surcharge and stem height, the cost and weight of wall increase. Also, the cost and weight objective functions decrease with increasing the soil unit weight. In addition, the Coulomb method gives lower cost and weight quantities than the Rankine method.