Optimizing Reinforced Concrete Cantilever Retaining Walls Using Artificial Bee Colony Algorithm

The Artificial Bee Colony (ABC) Algorithm is a sophisticated optimization technique that is inspired by the intelligent behaviors of honey bee swarms. These behaviors, such as foraging and communication within complex social structures, serve as the foundation for the algorithm's effectiveness. In this paper, the ABC algorithm is utilized to optimize the design of reinforced cantilever concrete retaining walls, with the goal of minimizing both cost and weight. The results are compared to existing literature, demonstrating the success of the ABC algorithm in achieving the objectives. Furthermore, a comparison is conducted between the optimized design and a conventional manual design, revealing a significant reduction in cost and weight through optimization. Additionally, two types of reinforced concrete cantilever retaining walls-a T-shape wall with variable stem thickness and a standard T-shape wall-are presented and compared, considering their differing variables and constraints. These comparisons are made for two objective functions: the cost and weight of the wall. To further investigate the impact of initial parameters, such as the unit weight of soil and stem height, a sensitivity analysis is conducted. The robustness of the ABC algorithm in optimizing the cost and weight of reinforced concrete cantilever retaining walls is demonstrated by the results.

کلیدواژه ها:

Retaining wall ، Bee colony algorithm ، optimization ، Wall cost and weight ، T-shape walls