2014
DOI: 10.7763/ijet.2014.v6.742
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Optimum Cost Design of Reinforced Concrete Retaining Walls Using Hybrid Firefly Algorithm

Abstract: Abstract-This paper develops a novel optimization method namely hybrid firefly algorithm with harmony search technique (IFA-HS), to obtain the optimal cost of the reinforced concrete retaining walls satisfying the stability criteria. The hybrid IFA-HS is utilized to find the economical design adhering to provisions of ACI 318-05. Also Coulomb lateral earth pressure theory is used to derive the lateral total thrust on the wall. Some design examples are tested using the new method. The results carried out on the… Show more

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Cited by 26 publications
(16 citation statements)
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“…Methods for obtaining cost and sizing equilibrium of reinforced concrete retaining walls have been the main objective of many studies over the years and continue to be relevant due to the developments in information and computer technologies. Metaheuristic algorithms such as the genetic algorithm (GA) [12,[26][27][28], big bang big crunch (BBBC) [29,30], particle swarm optimization (PSO) [31,32], firefly algorithm (FA) [33,34], harmony search (HS) algorithm [35,36], ant colony optimization (ACO), bat algorithm (BA) [37], charged system search (CSS) [38], simulated annealing (SA) [39][40][41], biogeography-based optimization algorithm (BBO) [42], teaching learning-based optimization (TLBO) [43], jaya algorithm (JA) [44], and flower pollination algorithm (FPA) [45] can be counted as the applied mew methods for the optimization process of retaining wall systems.…”
Section: Introductionmentioning
confidence: 99%
“…Methods for obtaining cost and sizing equilibrium of reinforced concrete retaining walls have been the main objective of many studies over the years and continue to be relevant due to the developments in information and computer technologies. Metaheuristic algorithms such as the genetic algorithm (GA) [12,[26][27][28], big bang big crunch (BBBC) [29,30], particle swarm optimization (PSO) [31,32], firefly algorithm (FA) [33,34], harmony search (HS) algorithm [35,36], ant colony optimization (ACO), bat algorithm (BA) [37], charged system search (CSS) [38], simulated annealing (SA) [39][40][41], biogeography-based optimization algorithm (BBO) [42], teaching learning-based optimization (TLBO) [43], jaya algorithm (JA) [44], and flower pollination algorithm (FPA) [45] can be counted as the applied mew methods for the optimization process of retaining wall systems.…”
Section: Introductionmentioning
confidence: 99%
“…Sezgisel optimizasyon yöntemlerinin gerçek çözümü garanti etmemekle birlikte kısa zamanda optimum sonuca yakınsayan güçlü ve etkili bir yöntem olması, basit yapısı ve kolaylıkla uygulanabilmesi sebebiyle konsol dayanma duvarlarının optimum tasarımlarının elde edilmesi ve maliyet analizlerinin yapılmasında yaygın olarak kullanılmaktadır. Benzetimli tavlama algoritması, parçacık sürü optimizasyonu, büyük patlama-büyük büzülme algoritması, ateş böceği algoritması, öğretme-öğrenme temelli optimizasyon algoritması, harmoni arama algoritması, gri kurt algoritması, yapay arı kolonisi algoritması ile yapılan bilimsel araştırmalar literatürde bulunan örneklerdir (Camp & Akin, 2012;Ceranic et al, 2001;Chau & Albermani, 2003;Dağdeviren & Kaymak, 2018;Kalemci et al, 2020;Khajehzadeh et al, 2010;Sheikholeslami et al, 2014;Temur & Bekdas, 2016;Uray et al, 2021). Konsol dayanma duvar tasarımında dinamik yük etkisi deprem bölgelerinde yapılacak olan tasarımlar için göz önünde bulundurulması gereken bir durumdur.…”
Section: Introductionunclassified
“…With regard to cost, it was found that the design gained by the method of heuristic optimization algorithms was half as expensive as the traditional design method. Sheikholeslami et al (2014) developed a novel optimization technique known as hybrid firefly algorithm with harmony search technique (IFA-HS) in order to obtain the optimal cost of reinforced concrete retaining walls satisfying the stability criteria and design provisions of ACI 318-05. Some design examples were tested using this new method from which the results confirmed the validity of the proposed algorithm.…”
Section: Introductionmentioning
confidence: 99%