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首页> 外文期刊>Journal of neurosurgical sciences >Optimal Design of Reinforced Concrete Cantilever Retaining Walls Utilizing Eleven Meta-Heuristic Algorithms: A Comparative Study
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Optimal Design of Reinforced Concrete Cantilever Retaining Walls Utilizing Eleven Meta-Heuristic Algorithms: A Comparative Study

机译：钢筋混凝土悬臂挡土墙优化设计利用11元启发式算法：比较研究

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摘要

In this paper, optimum design of reinforced concrete cantilever retaining walls is performed under static and dynamic loading conditions utilizing eleven population-based meta-heuristic algorithms. These algorithms consist of Artificial Bee Colony algorithm, Big Bang-Big Crunch algorithm, Teaching-Learning-Based Optimization algorithm, Imperialist Competitive Algorithm, Cuckoo Search algorithm, Charged System Search algorithm, Ray Optimization algorithm, Tug of War Optimization algorithm, Water Evaporation Optimization algorithm, Vibrating Particles System algorithm, and Cyclical Parthenogenesis Algorithm. Two well-known methods consisting of the Rankine and Coulomb methods are used to determine lateral earth pressures acting on cantilever retaining wall under static loading condition. In addition, Mononobe-Okabe method is employed for dynamic loading condition. The design is based on ACI 318-05 and the goal of optimization is to minimize the cost function of the cantilever retaining wall. The performance of the utilized algorithms is investigated through an optimization example of cantilever retaining wall. In addition, convergence histories of the algorithms are provided for better understanding of their performance.
机译：本文在静态和动态负载条件下进行了利用11种群体的荟萃启发式算法进行了钢筋混凝土悬臂挡土墙的最佳设计。这些算法包括人造群殖民地算法，大爆炸校准算法，教学 - 基于教学优化算法，帝国主义竞争算法，杜鹃搜索算法，充电系统搜索算法，射线优化算法，拔河优化算法，水蒸发优化算法，振动粒子系统算法和循环疗效算法。由Quankine和Coulomb方法组成的两个众所周知的方法用于确定在静态负载条件下作用于悬臂挡土墙的横向接地压力。此外，Mononobe-Okabe方法用于动态负载条件。该设计基于ACI 318-05，优化的目标是最小化悬臂挡土墙的成本函数。通过悬臂挡土墙的优化例研究了利用算法的性能。此外，提供了算法的收敛历史，以便更好地理解它们的性能。

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