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An Objective-Based Design Approach of Retaining Walls Using Cuckoo Search Algorithm

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Applications of Cuckoo Search Algorithm and its Variants

Part of the book series: Springer Tracts in Nature-Inspired Computing ((STNIC))

Abstract

In the past two decades, there has been ongoing trend to design retaining walls in an optimal way rather than the conventional trial and-error approach. In this study, reinforced concrete cantilever retaining wall is optimized using the Cuckoo Search (CS) algorithm, a metaheuristic swarm-based method that imitates the reproductive behavior of cuckoo birds. To obtain the optimal solution, design requirements are expressed as constraints to overcome violated solutions. Together with a mathematical definition of the objective function, three constraint groups are used to represent the geotechnical, structural, and geometrical design considerations. In addition, an objective-based design approach is introduced to optimize the cost and weight objective functions simultaneously. The performance of the CS is proved through its application on cantilever retaining walls, where two numerical examples are solved in terms of both cost and the weight of the walls. The results indicate that the CS is be a viable solution for the optimum design of retaining walls.

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Author information

Authors and Affiliations

  1. Civil Engineering Department, Middle East Technical University, Ankara, Turkey

    E. B. Tutuş & O. Pekcan

  2. Construction Department, University of Antwerp, Antwerp, Belgium

    T. Ghalandari

Authors
  1. E. B. Tutuş
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  2. T. Ghalandari
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  3. O. Pekcan
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Corresponding author

Correspondence to O. Pekcan .

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Editors and Affiliations

  1. Department of Information Technology, Techno International New Town, Kolkata, West Bengal, India

    Nilanjan Dey

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Tutuş, E.B., Ghalandari, T., Pekcan, O. (2021). An Objective-Based Design Approach of Retaining Walls Using Cuckoo Search Algorithm. In: Dey, N. (eds) Applications of Cuckoo Search Algorithm and its Variants. Springer Tracts in Nature-Inspired Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-5163-5_11

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