Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

2016 ◽  
Vol 49 (3) ◽  
pp. 381-400 ◽  
Author(s):  
Ibrahim Aydogdu
Keyword(s):  
Reinforced Concrete ◽  
Optimization Algorithm ◽  
Cost Optimization ◽  
Seismic Loading ◽  
Retaining Walls ◽  
Lévy Flights ◽  
Levy Flights ◽  
Cantilever Retaining Walls

scholarly journals Optimal Design of Reinforced Concrete Cantilever Retaining Walls Utilizing Eleven Meta-Heuristic Algorithms: A Comparative Study

2020 ◽  
Author(s):  
Ali Kaveh ◽  
Kiarash Biabani Hamedani ◽  
Taha Bakhshpoori
Keyword(s):  
Reinforced Concrete ◽  
Dynamic Loading ◽  
Optimization Algorithm ◽  
Loading Condition ◽  
Heuristic Algorithms ◽  
Search Algorithm ◽  
Retaining Wall ◽  
Retaining Walls ◽  
Water Evaporation ◽  
Cantilever Retaining Walls

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.

Optimum Design of Reinforced Concrete Retaining Walls

2018 ◽  
pp. 360-378
Author(s):  
Rasim Temür ◽  
Gebrail Bekdaş
Keyword(s):  
Reinforced Concrete ◽  
Optimum Design ◽  
Search Algorithm ◽  
Harmony Search ◽  
Minimum Cost ◽  
Retaining Walls ◽  
Slab Thickness ◽  
Construction Costs ◽  
Design Variables ◽  
Cantilever Retaining Walls

Methodologies based on metaheuristic algorithms such as particle swarm optimization, harmony search algorithm, and teaching-learning-based optimization are proposed for optimum design of reinforced concrete cantilever retaining walls. The objective function of optimization is to find a design providing minimum cost, including material and construction costs. For this purpose, the best combination of 11 design variables (heel and toe projections, stem thickness at the top and bottom of a wall, slab thickness and rebar diameters, and spacing between the bars) that satisfy 29 design constraints including stability (overturning, sliding, and bearing) and reinforced concrete design of the wall are searched during the optimization process. The rules of ACI 318 14 (building code requirements for structural concrete) are used for the reinforced concrete design. In order to determine the strengths and weaknesses of algorithms, several different cases are investigated. As conclusions, some suggestions have been obtained that will lead to future work in this field.

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