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Artificial intelligent support model for multiple criteria decision in construction management

Author

Listed:
  • Pham Vu Hong Son

    (Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM))

  • Luu Ngoc Quynh Khoi

    (Ho Chi Minh City University of Technology (HCMUT), Vietnam National University (VNU-HCM))

Abstract

In this study, the factors impacting building projects in Vietnam are discussed. A hybrid model, entitled Slime Mould Algorithm Opposition Tournament Mutation, which integrates Opposition-based learning methods, Tournament Selection and Mutation & Crossover, is used to address these aspects. The hybridization of this model boosts discoverability, promotes convergence, and minimizes local optimization to address the issue of simultaneously optimizing time, cost, quality, and CO2 trade-off problem. The project’s operating procedures are designed to produce the best results possible. Large-scale projects data will be simple to process using the hybrid model, allowing the proposed model to reach its full potential and provide the ideal solution. In addition to evaluating the proposed model, the authors also suggests comparing its results with the benchmarks for other algorithms, including the Slime Mould Algorithm, the multiple-objective Particle Swarm Optimization and the multiple-objective Artificial Bee Colony, in order to confirm its efficacy and achievement. The findings of this study therefore demonstrate that project managers can utilize the developed hybridization model to resolve optimization issues of significant building elements.

Suggested Citation

  • Pham Vu Hong Son & Luu Ngoc Quynh Khoi, 2024. "Artificial intelligent support model for multiple criteria decision in construction management," OPSEARCH, Springer;Operational Research Society of India, vol. 61(4), pages 2218-2241, December.
    • Handle: RePEc:spr:opsear:v:61:y:2024:i:4:d:10.1007_s12597-024-00749-1
    DOI: 10.1007/s12597-024-00749-1
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    References listed on IDEAS

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    1. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(C).
    2. Wesemeyer, Maximilian & Kamp, Johannes & Schmitz, Tillman & Müller, Daniel & Lakes, Tobia, 2023. "Multi-objective spatial optimization to balance trade-offs between farmland bird diversity and potential agricultural net returns," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 345, pages 1-10.
    3. Moura de Figueiredo, Nelio & Cavalcante Blanco, Claudio José & Pinheiro Campos Filho, Lúcio Carlos & Amarante Mesquita, André Luiz, 2023. "MUWOS - Multiple use water optimization system for the power generation and navigation trade-offs analysis," Renewable Energy, Elsevier, vol. 203(C), pages 205-218.
    4. Shoyab Ali & Annapurna Bhargava & Akash Saxena & Pavan Kumar, 2023. "A Hybrid Marine Predator Sine Cosine Algorithm for Parameter Selection of Hybrid Active Power Filter," Mathematics, MDPI, vol. 11(3), pages 1-25, January.
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