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.

翻译：在地震多发区域，钢筋混凝土悬臂式挡土墙的抗震性能至关重要。本研究采用水平和竖向拟静力系数对其抗震性能进行了分析。为考虑土压力引起的墙体自重及作用力，每个设计方案均关联了26项结构强度与岩土稳定性约束条件以及12个几何变量。这些约束与设计变量构成了一个十二维解空间的约束优化问题。为实现高效搜索并生成能够抵御地震灾害的可持续、经济且轻质的钢筋混凝土悬臂式挡土墙设计，本文提出了一种新颖的自适应模糊元启发式算法。该方法将搜索空间划分为子区域，并通过新型搜索组件建立勘探、信息共享与开发搜索能力。此外，采用模糊推理系统处理参数化与计算成本评估问题。结果表明，与多种经典及最优性能的设计优化器相比，该算法能够在九种地震工况下获得低成本、低自重且低二氧化碳排放的钢筋混凝土悬臂式挡土墙设计方案。