A set theoretical shuffled shepherd optimization algorithm for optimal design of cantilever retaining wall structures

In this paper, a recently developed meta-heuristic algorithm, shuffled shepherd optimization algorithm (SSOA), is employed for optimal design of reinforced concrete cantilever retaining wall structures under static and seismic loading conditions. The concepts of set theory are employed to express the SSOA in a set theoretical term. The Rankine and Coulomb theories are utilized in order to estimate the lateral earth pressures under the static loading condition, whereas the Mononobe-Okabe method is employed for the seismic one. Optimization aims to minimize the cost of cantilever retaining wall while satisfying some constraints on stability and strength limits. The design is based on the requirements of ACI 318-05. In order to investigate the efficiency of the SSOA, one benchmark cantilever retaining wall problem is considered from the literature. Comparing the optimization results obtained by the SSOA with those of other meta-heuristics shows the efficient performance of the SSOA in both aspects of accuracy and convergence rate.