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Statistical Evaluation of Metaheuristic Algorithm: An Optimum Reinforced Concrete T-beam Problem
Structural engineering is an area which have problems that are nonlinear in optimization. Due to that reason, metaheuristic methods are a major application source. In addition to finding the best suitable solution, different algorithms are needed to be verified and compared via statistical evaluation. In this chapter, optimum design of reinforced concrete (RC) beams that have design constraints formulated according to stress–strain capacity of members in the design regulations are investigated. Several metaheuristic algorithms such as harmony search (HS), teaching–learning-based optimization (TLBO), flower pollination algorithm (FPA) and Jaya algorithm (JA) are compared via statistical methods such as Friedman ranking, one-way ANOVA, post hoc Bonferroni test and independent samples t-test.
Statistical Evaluation of Metaheuristic Algorithm: An Optimum Reinforced Concrete T-beam Problem
Structural engineering is an area which have problems that are nonlinear in optimization. Due to that reason, metaheuristic methods are a major application source. In addition to finding the best suitable solution, different algorithms are needed to be verified and compared via statistical evaluation. In this chapter, optimum design of reinforced concrete (RC) beams that have design constraints formulated according to stress–strain capacity of members in the design regulations are investigated. Several metaheuristic algorithms such as harmony search (HS), teaching–learning-based optimization (TLBO), flower pollination algorithm (FPA) and Jaya algorithm (JA) are compared via statistical methods such as Friedman ranking, one-way ANOVA, post hoc Bonferroni test and independent samples t-test.
Statistical Evaluation of Metaheuristic Algorithm: An Optimum Reinforced Concrete T-beam Problem
Studies in Systems, Decision and Control
Nigdeli, Sinan Melih (Herausgeber:in) / Bekdaş, Gebrail (Herausgeber:in) / Kayabekir, Aylin Ece (Herausgeber:in) / Yucel, Melda (Herausgeber:in) / Kayabekir, Aylin Ece (Autor:in) / Nigdeli, Müge (Autor:in)
05.12.2020
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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