Acceso abierto

Dynamic Cost Estimation and Optimization Strategy in Engineering Cost Combining Reinforcement Learning

  
11 abr 2025

Cite
Descargar portada

Deliu, N. (2024). Reinforcement learning for sequential decision making in population research. Quality & Quantity, 58(6), 5057-5080. https://doi.org/10.1007/s11135-023-01755-z Deliu N. ( 2024 ). Reinforcement learning for sequential decision making in population research . Quality & Quantity , 58 ( 6 ), 5057 - 5080 . https://doi.org/10.1007/s11135-023-01755-z Search in Google Scholar

Tayefeh Hashemi, S., Ebadati, O. M., & Kaur, H. (2020). Cost estimation and prediction in construction projects: A systematic review on machine learning techniques. SN Applied Sciences, 2(10), 1703. https://doi.org/10.1007/s42452-020-03497-1 Tayefeh Hashemi S. Ebadati O. M. Kaur H. ( 2020 ). Cost estimation and prediction in construction projects: A systematic review on machine learning techniques . SN Applied Sciences , 2 ( 10 ), 1703 . https://doi.org/10.1007/s42452-020-03497-1 Search in Google Scholar

Jiang, C., Li, X., Lin, J. R., Liu, M., & Ma, Z. (2023). Adaptive control of resource flow to optimize construction work and cash flow via online deep reinforcement learning. Automation in Construction, 150, 104817. https://doi.org/10.1016/j.autcon.2023.104817 Jiang C. Li X. Lin J. R. Liu M. Ma Z. ( 2023 ). Adaptive control of resource flow to optimize construction work and cash flow via online deep reinforcement learning . Automation in Construction , 150 , 104817 . https://doi.org/10.1016/j.autcon.2023.104817 Search in Google Scholar

Hu, H., Jiang, S., Goswami, S. S., & Zhao, Y. (2024). Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering. Information, 15(5), 280. https://doi.org/10.3390/info15050280 Hu H. Jiang S. Goswami S. S. Zhao Y. ( 2024 ). Fuzzy Integrated Delphi-ISM-MICMAC Hybrid Multi-Criteria Approach to Optimize the Artificial Intelligence (AI) Factors Influencing Cost Management in Civil Engineering . Information , 15 ( 5 ), 280 . https://doi.org/10.3390/info15050280 Search in Google Scholar

Liu, Y. T., Yang, J. M., Chen, L., Guo, T., & Jiang, Y. (2020, August). Overview of reinforcement learning based on value and policy. In 2020 Chinese Control And Decision Conference (CCDC) (pp. 598-603). IEEE. https://doi.org/10.1109/CCDC49329.2020.9164615 Liu Y. T. Yang J. M. Chen L. Guo T. Jiang Y. ( 2020 , August ). Overview of reinforcement learning based on value and policy . In 2020 Chinese Control And Decision Conference (CCDC) (pp. 598 - 603 ). IEEE . https://doi.org/10.1109/CCDC49329.2020.9164615 Search in Google Scholar

Zhang, Y. (2024). Research on the Application of Artificial Intelligence-based Cost Estimation and Cost Control Methods in Green Buildings. Scalable Computing: Practice and Experience, 25(6), 4772-4779. https://doi.org/10.12694/scpe.v25i6.3293 Zhang Y. ( 2024 ). Research on the Application of Artificial Intelligence-based Cost Estimation and Cost Control Methods in Green Buildings . Scalable Computing: Practice and Experience , 25 ( 6 ), 4772 - 4779 . https://doi.org/10.12694/scpe.v25i6.3293 Search in Google Scholar

Birim, S., Kazancoglu, I., Mangla, S. K., Kahraman, A., & Kazancoglu, Y. (2024). The derived demand for advertising expenses and implications on sustainability: A comparative study using deep learning and traditional machine learning methods. Annals of Operations Research, 339(1), 131-161. https://doi.org/10.1007/s10479-021-04429-x Birim S. Kazancoglu I. Mangla S. K. Kahraman A. Kazancoglu Y. ( 2024 ). The derived demand for advertising expenses and implications on sustainability: A comparative study using deep learning and traditional machine learning methods . Annals of Operations Research , 339 ( 1 ), 131 - 161 . https://doi.org/10.1007/s10479-021-04429-x Search in Google Scholar

Daneva, M. (2010). Balancing uncertainty of context in ERP project estimation: an approach and a case study. Journal of Software Maintenance and Evolution: Research and Practice, 22(5), 329-357. https://doi.org/10.1002/smr.466 Daneva M. ( 2010 ). Balancing uncertainty of context in ERP project estimation: an approach and a case study . Journal of Software Maintenance and Evolution: Research and Practice , 22 ( 5 ), 329 - 357 . https://doi.org/10.1002/smr.466 Search in Google Scholar

Karadimos, P., & Anthopoulos, L. (2024). A taxonomy of machine learning techniques for construction cost estimation. Innovative Infrastructure Solutions, 9(11), 420. https://doi.org/10.1007/s41062-024-01705-0 Karadimos P. Anthopoulos L. ( 2024 ). A taxonomy of machine learning techniques for construction cost estimation . Innovative Infrastructure Solutions , 9 ( 11 ), 420 . https://doi.org/10.1007/s41062-024-01705-0 Search in Google Scholar

Abd Elaziz, M., Dahou, A., Abualigah, L., Yu, L., Alshinwan, M., Khasawneh, A. M., & Lu, S. (2021). Advanced metaheuristic optimization techniques in applications of deep neural networks: a review. Neural Computing and Applications, 1-21. https://doi.org/10.1007/s00521-021-05960-5 Abd Elaziz M. Dahou A. Abualigah L. Yu L. Alshinwan M. Khasawneh A. M. Lu S. ( 2021 ). Advanced metaheuristic optimization techniques in applications of deep neural networks: a review . Neural Computing and Applications , 1 - 21 . https://doi.org/10.1007/s00521-021-05960-5 Search in Google Scholar

Merckx, G., & Chaturvedi, A. (2020). Short vs. long-term procurement contracts when supplier can invest in cost reduction. International Journal of Production Economics, 227, 107652. https://doi.org/10.1016/j.ijpe.2020.107652 Merckx G. Chaturvedi A. ( 2020 ). Short vs. long-term procurement contracts when supplier can invest in cost reduction . International Journal of Production Economics , 227 , 107652 . https://doi.org/10.1016/j.ijpe.2020.107652 Search in Google Scholar

Nian, R., Liu, J., & Huang, B. (2020). A review on reinforcement learning: Introduction and applications in industrial process control. Computers & Chemical Engineering, 139, 106886. https://doi.org/10.1016/j.compchemeng.2020.106886 Nian R. Liu J. Huang B. ( 2020 ). A review on reinforcement learning: Introduction and applications in industrial process control . Computers & Chemical Engineering , 139 , 106886 . https://doi.org/10.1016/j.compchemeng.2020.106886 Search in Google Scholar

Brown, N. K., Garland, A. P., Fadel, G. M., & Li, G. (2022). Deep reinforcement learning for engineering design through topology optimization of elementally discretized design domains. Materials & Design, 218, 110672. https://doi.org/10.1016/j.matdes.2022.110672 Brown N. K. Garland A. P. Fadel G. M. Li G. ( 2022 ). Deep reinforcement learning for engineering design through topology optimization of elementally discretized design domains . Materials & Design , 218 , 110672 . https://doi.org/10.1016/j.matdes.2022.110672 Search in Google Scholar

Barto, A. G. (2021). Reinforcement Learning: An Introduction. SIAM Rev, 6(2), 423. https://doi.org/10.1137/21N975254 Barto A. G. ( 2021 ). Reinforcement Learning: An Introduction. SIAM Rev , 6 ( 2 ), 423 . https://doi.org/10.1137/21N975254 Search in Google Scholar

Zhang, W., Wang, J., Liu, Y., Gao, G., Liang, S., & Ma, H. (2020). Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery. Applied Energy, 275, 115401. https://doi.org/10.1016/j.apenergy.2020.115401 Zhang W. Wang J. Liu Y. Gao G. Liang S. Ma H. ( 2020 ). Reinforcement learning-based intelligent energy management architecture for hybrid construction machinery . Applied Energy , 275 , 115401 . https://doi.org/10.1016/j.apenergy.2020.115401 Search in Google Scholar

Elmousalami, H. H. (2020). Comparison of artificial intelligence techniques for project conceptual cost prediction: A case study and comparative analysis. IEEE Transactions on Engineering Management, 68(1), 183-196. https://doi.org/10.1109/TEM.2020.2972078 Elmousalami H. H. ( 2020 ). Comparison of artificial intelligence techniques for project conceptual cost prediction: A case study and comparative analysis . IEEE Transactions on Engineering Management , 68 ( 1 ), 183 - 196 . https://doi.org/10.1109/TEM.2020.2972078 Search in Google Scholar

Draz, M. M., Emam, O., & Azzam, S. M. (2024). Software cost estimation predication using a convolutional neural network and particle swarm optimization algorithm. Scientific Reports, 14(1), 13129. https://doi.org/10.1038/s41598-024-63025-8 Draz M. M. Emam O. Azzam S. M. ( 2024 ). Software cost estimation predication using a convolutional neural network and particle swarm optimization algorithm . Scientific Reports , 14 ( 1 ), 13129 . https://doi.org/10.1038/s41598-024-63025-8 Search in Google Scholar

Yet, B., Constantinou, A., Fenton, N., Neil, M., Luedeling, E., & Shepherd, K. (2016). A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study. Expert Systems with Applications, 60, 141-155. https://doi.org/10.1016/j.eswa.2016.05.005 Yet B. Constantinou A. Fenton N. Neil M. Luedeling E. Shepherd K. ( 2016 ). A Bayesian network framework for project cost, benefit and risk analysis with an agricultural development case study . Expert Systems with Applications , 60 , 141 - 155 . https://doi.org/10.1016/j.eswa.2016.05.005 Search in Google Scholar

ul Hassan, C. A., Khan, M. S., Irfan, R., Iqbal, J., Hussain, S., Sajid Ullah, S., … & Umar, F. (2022). Optimizing Deep Learning Model for Software Cost Estimation Using Hybrid Meta-Heuristic Algorithmic Approach. Computational Intelligence and Neuroscience, 2022(1), 3145956. https://doi.org/10.1155/2022/3145956 ul Hassan C. A. Khan M. S. Irfan R. Iqbal J. Hussain S. Sajid Ullah S. Umar F. ( 2022 ). Optimizing Deep Learning Model for Software Cost Estimation Using Hybrid Meta‐Heuristic Algorithmic Approach . Computational Intelligence and Neuroscience , 2022 ( 1 ), 3145956 . https://doi.org/10.1155/2022/3145956 Search in Google Scholar

Pan, S. J., & Yang, Q. (2009). A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345-1359. https://doi.org/10.1109/TKDE.2009.191 Pan S. J. Yang Q. ( 2009 ). A survey on transfer learning . IEEE Transactions on Knowledge and Data Engineering , 22 ( 10 ), 1345 - 1359 . https://doi.org/10.1109/TKDE.2009.191 Search in Google Scholar

Kruekaew, B., & Kimpan, W. (2022). Multi-objective task scheduling optimization for load balancing in cloud computing environment using hybrid artificial bee colony algorithm with reinforcement learning. IEEE Access, 10, 17803-17818. https://doi.org/10.1109/ACCESS.2022.3149955 Kruekaew B. Kimpan W. ( 2022 ). Multi-objective task scheduling optimization for load balancing in cloud computing environment using hybrid artificial bee colony algorithm with reinforcement learning . IEEE Access , 10 , 17803 - 17818 . https://doi.org/10.1109/ACCESS.2022.3149955 Search in Google Scholar

Paraschos, P. D., Koulinas, G. K., & Koulouriotis, D. E. (2024). Reinforcement Learning-Based Optimization for Sustainable and Lean Production within the Context of Industry 4.0. Algorithms, 17(3), 98. https://doi.org/10.3390/a17030098 Paraschos P. D. Koulinas G. K. Koulouriotis D. E. ( 2024 ). Reinforcement Learning-Based Optimization for Sustainable and Lean Production within the Context of Industry 4.0 . Algorithms , 17 ( 3 ), 98 . https://doi.org/10.3390/a17030098 Search in Google Scholar

Li, L., Fan, Y., Tse, M., & Lin, K. Y. (2020). A review of applications in federated learning. Computers & Industrial Engineering, 149, 106854. https://doi.org/10.1016/j.cie.2020.106854 Li L. Fan Y. Tse M. Lin K. Y. ( 2020 ). A review of applications in federated learning . Computers & Industrial Engineering , 149 , 106854 . https://doi.org/10.1016/j.cie.2020.106854 Search in Google Scholar