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. Manuscript profile

In this paper, cost and weight optimization for reinforcement cantilever concrete retaining wall is investigated using intelligent water drops algorithm (IWDA). The algorithm capability was compared with that of others in the literature. A computer program has been developed to analyze reinforced concrete cantilever retaining walls using the IWDA algorithm. The results show that the IWDA algorithm is able to optimize retaining walls from viewpoints of cost and weight. The effect of the wall geometry has been investigated by considering four types of T-shape walls in order to discover the influence of contributing variables on objective functions. It has been found that backfill slope, unit weight and friction angle are important parameters affecting retaining wall cost and weight. Also, the Coulomb method in computing lateral earth pressure on retaining walls leads to lower cost and weight for retaining walls than the Rankine method. In general, optimizing retaining walls may lead to approximately 44 percent saving. Manuscript profile