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Optimum design of gravity and reinforced retaining walls using enhanced charged system search algorithm
Abstract This paper develops a methodology to obtain the optimum design of the gravity and reinforced cantilever retaining walls in terms of least-cost, having different cases of backfill satisfying the stability criteria, according to the height and properties of earth that the wall are required to support. An Enhanced Charged System Search Algorithm (ECSS) is utilized to find the economical sections as the output after minimizing the cost. The ECSS is one of the recently developed meta-heuristic algorithms that is inspired by the Coulomb and Gauss’s laws of electrostatics in physics. In order to evaluate the efficiency of this algorithm, some numerical examples are utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the ECSS.
Optimum design of gravity and reinforced retaining walls using enhanced charged system search algorithm
Abstract This paper develops a methodology to obtain the optimum design of the gravity and reinforced cantilever retaining walls in terms of least-cost, having different cases of backfill satisfying the stability criteria, according to the height and properties of earth that the wall are required to support. An Enhanced Charged System Search Algorithm (ECSS) is utilized to find the economical sections as the output after minimizing the cost. The ECSS is one of the recently developed meta-heuristic algorithms that is inspired by the Coulomb and Gauss’s laws of electrostatics in physics. In order to evaluate the efficiency of this algorithm, some numerical examples are utilized. Comparing the results of the retaining wall designs obtained by the other methods illustrates a good performance of the ECSS.
Optimum design of gravity and reinforced retaining walls using enhanced charged system search algorithm
Talatahari, S. (author) / Sheikholeslami, R. (author)
KSCE Journal of Civil Engineering ; 18 ; 1464-1469
2014-06-01
6 pages
Article (Journal)
Electronic Resource
English
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