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Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls

Author

Listed:
  • Víctor Yepes

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain
    These authors contributed equally to this work.)

  • José V. Martí

    (Institute of Concrete Science and Technology (ICITECH), Universitat Politècnica de València, 46022 València, Spain
    These authors contributed equally to this work.)

  • José García

    (Pontificia Universidad Católica de Valparaíso, 2362807 Valparaíso, Chile
    These authors contributed equally to this work.)

Abstract

The optimization of the cost and CO 2 emissions in earth-retaining walls is of relevance, since these structures are often used in civil engineering. The optimization of costs is essential for the competitiveness of the construction company, and the optimization of emissions is relevant in the environmental impact of construction. To address the optimization, black hole metaheuristics were used, along with a discretization mechanism based on min–max normalization. The stability of the algorithm was evaluated with respect to the solutions obtained; the steel and concrete values obtained in both optimizations were analyzed. Additionally, the geometric variables of the structure were compared. Finally, the results obtained were compared with another algorithm that solved the problem. The results show that there is a trade-off between the use of steel and concrete. The solutions that minimize CO 2 emissions prefer the use of concrete instead of those that optimize the cost. On the other hand, when comparing the geometric variables, it is seen that most remain similar in both optimizations except for the distance between buttresses. When comparing with another algorithm, the results show a good performance in optimization using the black hole algorithm.

Suggested Citation

  • Víctor Yepes & José V. Martí & José García, 2020. "Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls," Sustainability, MDPI, vol. 12(7), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2767-:d:339763
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    References listed on IDEAS

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    1. Dongyoun Lee & Goune Kang & Chulu Nam & Hunhee Cho & Kyung-In Kang, 2019. "Stochastic Analysis of Embodied Carbon Dioxide Emissions Considering Variability of Construction Sites," Sustainability, MDPI, vol. 11(15), pages 1-12, August.
    2. Xiaochuan Shi & Lei Wu & Xiaoliang Meng, 2017. "A New Optimization Model for the Sustainable Development: Quadratic Knapsack Problem with Conflict Graphs," Sustainability, MDPI, vol. 9(2), pages 1-10, February.
    3. Kun Lu & Xiaoyan Jiang & Vivian W. Y. Tam & Mengyun Li & Hongyu Wang & Bo Xia & Qing Chen, 2019. "Development of a Carbon Emissions Analysis Framework Using Building Information Modeling and Life Cycle Assessment for the Construction of Hospital Projects," Sustainability, MDPI, vol. 11(22), pages 1-18, November.
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    Cited by:

    1. Aylin Ece Kayabekir & Zülal Akbay Arama & Gebrail Bekdaş & Sinan Melih Nigdeli & Zong Woo Geem, 2020. "Eco-Friendly Design of Reinforced Concrete Retaining Walls: Multi-objective Optimization with Harmony Search Applications," Sustainability, MDPI, vol. 12(15), pages 1-30, July.
    2. Zülal Akbay Arama & Aylin Ece Kayabekir & Gebrail Bekdaş & Zong Woo Geem, 2020. "CO 2 and Cost Optimization of Reinforced Concrete Cantilever Soldier Piles: A Parametric Study with Harmony Search Algorithm," Sustainability, MDPI, vol. 12(15), pages 1-25, July.
    3. Khalid Almutairi & Salem Algarni & Talal Alqahtani & Hossein Moayedi & Amir Mosavi, 2022. "A TLBO-Tuned Neural Processor for Predicting Heating Load in Residential Buildings," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    4. José García & Victor Yepes & José V. Martí, 2020. "A Hybrid k-Means Cuckoo Search Algorithm Applied to the Counterfort Retaining Walls Problem," Mathematics, MDPI, vol. 8(4), pages 1-22, April.
    5. José García & José V. Martí & Víctor Yepes, 2020. "The Buttressed Walls Problem: An Application of a Hybrid Clustering Particle Swarm Optimization Algorithm," Mathematics, MDPI, vol. 8(6), pages 1-22, May.
    6. José García & Gino Astorga & Víctor Yepes, 2021. "An Analysis of a KNN Perturbation Operator: An Application to the Binarization of Continuous Metaheuristics," Mathematics, MDPI, vol. 9(3), pages 1-20, January.
    7. Zenonas Turskis & Kęstutis Urbonas & Danutė Sližytė & Jurgis Medzvieckas & Rimantas Mackevičius & Vaidotas Šapalas, 2020. "A Novel Integrated Approach to Solve Industrial Ground Floor Design Problems," Sustainability, MDPI, vol. 12(12), pages 1-13, June.
    8. Marcelo Becerra-Rozas & José Lemus-Romani & Felipe Cisternas-Caneo & Broderick Crawford & Ricardo Soto & Gino Astorga & Carlos Castro & José García, 2022. "Continuous Metaheuristics for Binary Optimization Problems: An Updated Systematic Literature Review," Mathematics, MDPI, vol. 11(1), pages 1-32, December.
    9. Cleovir José Milani & Víctor Yepes & Moacir Kripka, 2020. "Proposal of Sustainability Indicators for the Design of Small-Span Bridges," IJERPH, MDPI, vol. 17(12), pages 1-23, June.

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