Hybrid Bat &amp; Particle Swarm Algorithm for optimization of labyrinth spillway based on half &amp; quarter round crest shapes

Ferdowsi, Ahmad; Farzin, Saeed; Mousavi, Sayed‐Farhad; Karami, Hojat

doi:10.1016/j.flowmeasinst.2019.03.003

Cited by 23 publications

(11 citation statements)

References 19 publications

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“…According to (1) and the findings from earlier studies [17], [18], [22]- [26], Cd is the most sensitive parameter in Q calculations. The Cd is a function of several other prominent parameters [27].…”

Section: Labyrinth Weirmentioning

confidence: 86%

“…Where Ht/P is the water head ratio; a, b, c, and d are constants that have been proposed for different α angles [18], [28]. It is noteworthy that this equation has been utilized in all the previous LW optimization researches [15]- [17], [19].…”

Section: Labyrinth Weirmentioning

confidence: 99%

“…In other words, with a minimum volume of concrete, the labyrinth can approach the minimum cost. The total concrete volume in an LW can be calculated by the following equations [15]- [17], [19]:…”

Section: Labyrinth Weirmentioning

confidence: 99%

“…Ute dam weir is one of the most significant LWs in the world. Many researchers in the LW studies, particularly in LW optimization approaches, considered the Ute dam LW a case study [15]- [17], [19], [28]. Hence, this specific weir can be considered as a benchmark in this area.…”

Section: Case Study: Ute Dammentioning

confidence: 99%

“…Their optimal solution reduced the concrete consumption of Ute LW by 21.47%. Ferdowsi et al [17] investigated half-round and quarter-round crest shapes in the optimal design of Ute dam LW. They proposed a hybrid bat and PSO algorithm to minimize the construction cost of LW (i.e., concrete consumption).…”

Section: Introductionmentioning

confidence: 99%

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An Improved Multi-Objective Particle Swarm Optimization With TOPSIS and Fuzzy Logic for Optimizing Trapezoidal Labyrinth Weir

et al. 2021

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Labyrinth Weir (LW) is a popular control structure that passes a significantly higher flow rate compared to the linear weirs. In order to approach the optimal design of a trapezoidal LW, a multi-objective problem is defined to concurrently minimize the LW consumed concrete volume and maximize its discharge capacity. Simultaneously, a Radial Basis function Neural Networks (RBFNN) is designed and used for estimating LW discharge coefficient (Cd) according to the existing experimental results. An improved multi-objective particle swarm optimization (MOPSO) algorithm named TOPSIS Fuzzy MOPSO (TFMOPSO) is proposed to solve the LW optimization problem. This algorithm utilizes the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank the solutions, while a fuzzy inference system is developed to select the algorithm strategy for finding two leaders among the non-dominated solutions. The performance of the proposed TFMOPSO has been tested on the optimization problem of the LW of the Ute dam. The results of TFMOPSO, along with three other state-of-the-art multi-objective algorithms, are explored in terms of hypervolume, coverage, and spacing metrics. It is demonstrated that the TFMOPSO outperforms other algorithms and studies for solving the LW multi-objective optimization problem for the case of Ute dam. Also, RBFNN is found to be one of the most appropriate approaches among studied algorithms in estimating the discharge coefficient of LW, while Pareto optimal solutions from TFMOPSO exhibit a significant improvement compared to the original design of Ute dam LW.

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Section: Labyrinth Weirmentioning

confidence: 86%