Charged System Search Algorithm for the Optimum Cost Design of Reinforced Concrete Cantilever Retaining Walls

2012 ◽  
Vol 38 (3) ◽  
pp. 563-570 ◽  
Author(s):  
A. Kaveh ◽  
A. F. Behnam
Keyword(s):  
Reinforced Concrete ◽  
Search Algorithm ◽  
Retaining Walls ◽  
Charged System Search ◽  
Charged System ◽  
Cantilever Retaining Walls ◽  
Optimum Cost

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.

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.

scholarly journals Optimum Design of Gravity Retaining Walls Using Charged System Search Algorithm

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Talatahari ◽  
R. Sheikholeslami ◽  
M. Shadfaran ◽  
M. Pourbaba
Keyword(s):  
Optimum Design ◽  
Search Algorithm ◽  
Retaining Wall ◽  
Earth Pressure ◽  
Retaining Walls ◽  
Stone Masonry ◽  
Charged System Search ◽  
Charged System ◽  
Major Factors ◽  
The Cost

This study focuses on the optimum design retaining walls, as one of the familiar types of the retaining walls which may be constructed of stone masonry, unreinforced concrete, or reinforced concrete. The material cost is one of the major factors in the construction of gravity retaining walls therefore, minimizing the weight or volume of these systems can reduce the cost. To obtain an optimal seismic design of such structures, this paper proposes a method based on a novel meta-heuristic algorithm. The algorithm is inspired by the Coulomb's and Gauss’s laws of electrostatics in physics, and it is called charged system search (CSS). In order to evaluate the efficiency of this algorithm, an example is utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the CSS. In this paper, we used the Mononobe-Okabe method which is one of the pseudostatic approaches to determine the dynamic earth pressure.

Novel Adaptive Charged System Search algorithm for optimal tuning of fuzzy controllers

2014 ◽  
Vol 41 (4) ◽  
pp. 1168-1175 ◽  
Author(s):  
Radu-Emil Precup ◽  
Radu-Codruţ David ◽  
Emil M. Petriu ◽  
Stefan Preitl ◽  
Mircea-Bogdan Rădac
Keyword(s):  
Search Algorithm ◽  
Fuzzy Controllers ◽  
Optimal Tuning ◽  
Charged System Search ◽  
Charged System
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