Volume 16, Issue 3 (7-2026)
IJOCE 2026, 16(3): 337-353 |
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Paudel A, Chhetri S. Advances in Optimization of Dams: A State of The Art Review. IJOCE 2026; 16 (3) :337-353
URL: http://ijoce.iust.ac.ir/article-1-673-en.html
URL: http://ijoce.iust.ac.ir/article-1-673-en.html
1- Department of Civil Engineering, Pulchowk Campus, Lalitpur, Nepal
2- Ministry of Infrastructure Development, Government of Nepal
2- Ministry of Infrastructure Development, Government of Nepal
Abstract: (479 Views)
Optimization strategies have turned out to be a requirement in the design and construction of dams because of the increasing demand for water resources, hydropower generation, and flood control and due to the inbuilt high cost and complexities of such massive structures (1) (2) (3) (4) (5) (6) (7) . This review paper summarizes recent advances on dam optimization, covering a broad scope of dam types, primary objectives, approaches, and performance evaluation indices. It highlights the vast transition from traditional, at times time-consuming, trial-and-error based design techniques and classical optimization methods to efficient meta-heuristic (MH) and hybrid algorithms that outperform in terms of efficiency, accuracy, and global exploration (1) (3) (8) . The paper also touches upon the growing application of Reliability-Based Design Optimization (RBDO) and robust optimization towards dealing with material property uncertainty, loading, and environmental uncertainties to achieve safer and cost-efficient designs (9) (10) (11) . Ideal optimization objectives, such as volume reduction of concrete and dam safety maximization, are explored along with several geometric, stress, stability, and frequency constraints. Finally, it discusses the ongoing problems, including the computational expense and selection of appropriate algorithms, and instilling future research directions essential for further advancement of dam engineering practice.
Keywords: Meta-heuristic Algorithms, Reliability-Based Design Optimization (RBDO), Hydraulic Infrastructure
Type of Study: Research |
Subject:
Optimal design
Received: 2026/05/24 | Accepted: 2026/07/21 | Published: 2026/07/23
Received: 2026/05/24 | Accepted: 2026/07/21 | Published: 2026/07/23
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