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A platform for research: civil engineering, architecture and urbanism
Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm
Retaining walls need to be designed optimally since huge cost savings are probable considering their dimensions and materials used in the design and construction. Even better savings are possible when they are constructed in earthquake-prone regions. In this study, an improved flower pollination algorithm (IFPA) is used to optimize the design of the reinforced concrete cantilever retaining wall subjected to dynamic loadings. The mathematical model contains three constraints including geotechnical, structural, and geometrical considerations. As the previous FPA applications revealed the efficiency of this method for retaining wall problems, some modifications have been made on the existing method when dynamic loadings are included. To reveal the performance of IFPA, sensitivity analyses are carried out using a variety of soil parameters. Also, tuning of IFPA parameters is illustrated with two different retaining wall case studies reported in the literature. The results indicate that IFPA is a viable alternative to the well-known metaheuristics. This study also reveals that there is space for further improvements to cover wider range of geotechnical engineering-related optimization problems.
Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm
Retaining walls need to be designed optimally since huge cost savings are probable considering their dimensions and materials used in the design and construction. Even better savings are possible when they are constructed in earthquake-prone regions. In this study, an improved flower pollination algorithm (IFPA) is used to optimize the design of the reinforced concrete cantilever retaining wall subjected to dynamic loadings. The mathematical model contains three constraints including geotechnical, structural, and geometrical considerations. As the previous FPA applications revealed the efficiency of this method for retaining wall problems, some modifications have been made on the existing method when dynamic loadings are included. To reveal the performance of IFPA, sensitivity analyses are carried out using a variety of soil parameters. Also, tuning of IFPA parameters is illustrated with two different retaining wall case studies reported in the literature. The results indicate that IFPA is a viable alternative to the well-known metaheuristics. This study also reveals that there is space for further improvements to cover wider range of geotechnical engineering-related optimization problems.
Optimizing Reinforced Cantilever Retaining Walls Under Dynamic Loading Using Improved Flower Pollination Algorithm
Springer Tracts in Nature-Inspired Computing
Dey, Nilanjan (editor) / Tutuş, E. B. (author) / Pekcan, O. (author) / Altun, M. (author) / Türkezer, M. (author)
2021-03-18
31 pages
Article/Chapter (Book)
Electronic Resource
English
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