  In earthquake-prone zones, the seismic performance of reinforced concrete
cantilever (RCC) retaining walls is significant. In this study, the seismic
performance was investigated using horizontal and vertical pseudo-static
coefficients. To tackle RCC weights and forces resulting from these earth
pressures, 26 constraints for structural strengths and geotechnical stability
along with 12 geometric variables are associated with each design. These
constraints and design variables form a constraint optimization problem with a
twelve-dimensional solution space. To conduct effective search and produce
sustainable, economical, lightweight RCC designs robust against earthquake
hazards, a novel adaptive fuzzy-based metaheuristic algorithm is applied. The
proposed method divides the search space to sub-regions and establishes
exploration, information sharing, and exploitation search capabilities based on
its novel search components. Further, fuzzy inference systems were employed to
address parameterization and computational cost evaluation issues. It was found
that the proposed algorithm can achieve low-cost, low-weight, and low CO2
emission RCC designs under nine seismic conditions in comparison with several
classical and best-performing design optimizers.
