A Novel Approach to Supply the Water Reservoir Demand Based on a Hybrid Whale Optimization Algorithm

Donyaii, Alireza; Sarraf, Amirpouya; Ahmadi, Hassan

doi:10.1155/2020/8833866

Cited by 14 publications

(7 citation statements)

References 41 publications

(55 reference statements)

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“…which means that it has the lowest capability to recover and return to normal operation in the case of a system failure (Sharifi et al 2021;Donyaii et al 2020). The most resilient model is determined to be WOA, as it has the best CV.…”

Section: Resultsmentioning

confidence: 99%

Investigating dam reservoir operation optimization using metaheuristic algorithms

et al. 2022

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The optimization of dam reservoir operations is of the utmost importance, as operators strive to maximize revenue while minimizing expenses, risks, and deficiencies. Metaheuristics have recently been investigated extensively by researchers in the management of dam reservoirs. But the animal-concept-based metaheuristic algorithm with Lévy flight integration approach has not been used at Karun-4. This paper investigates the optimization of dam reservoir operation using three unexplored metaheuristics: the whale optimization algorithm (WOA), the Levy-flight WOA (LFWOA), and the Harris hawks optimization algorithm (HHO). Utilizing a time series data set on the hydrological and climatic characteristics of the Karun-4 hydroelectric reservoir in Iran, an analysis was conducted. The objective functions and constraints of the Karun-4 hydropower reservoir were examined throughout the optimization procedure. HHO produces the best optimal value, the least-worst optimal value, the best average optimal value, and the best standard deviation (SD) with scores of 0.000026, 0.001735, 0.000520, and 0.000614, respectively, resulting in the best overall ranking mean (RM) with a score of 1.5 at Karun-4. Throughout the duration of the test, the optimized trends of water release and water storage indicate that HHO is superior to the other investigated metaheuristics. WOA has the best correlation of variation (CV) with a score of 0.090195, while LFWOA has the best convergence rate (3.208 s) and best CPU time. Overall, it can be concluded that HHO has the most desirable performance in terms of optimization. Yet, current studies indicate that both WOA and LFWOA generate positive and comparable outcomes.

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Section: Resultsmentioning

confidence: 99%

Investigating dam reservoir operation optimization using metaheuristic algorithms

et al. 2022

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“…Mixing different algorithms could help overcome the shortcomings of a single algorithm and solve problems more efficiently [23]. The improved algorithms of these algorithms are hybrid whale optimization algorithm [30], hybrid algorithm of invasive weed optimization and cuckoo search algorithm [23], hybrid slime mold and arithmetic optimization algorithm [31], and so on. These are widely used in reservoir optimal operation problems, including short-term [32,33], medium-and long-term optimal operation [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Cascade Reservoir Operation for Power Generation, Based on an Improved Lightning Search Algorithm

Tao,

Mo,

Yang

et al. 2023

Water

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Cascade reservoir operation can ensure the optimal use of water and hydro-energy resources and improve the overall efficiency of hydropower stations. A large number of studies have used meta-heuristic algorithms to optimize reservoir operation, but there are still problems such as the inability to find a global optimal solution and slow convergence speed. Lightning search algorithm (LSA) is a new meta-heuristic algorithm, which has the advantages such as high convergence speed and few parameters to be adjusted. However, there is no study on the application of LSA in reservoir operation. In this paper, LSA is used to solve the problem of reservoir operation optimization to verify its feasibility. We also propose an improved LSA algorithm, the frog-leaping–particle swarm optimization–LSA (FPLSA), which was improved by using multiple strategies, and we address the shortcomings of LSA such as low solution accuracy and the tendency to fall into local optima. After preliminary verification of ten test functions, the effect is significantly enhanced. Using the lower Jinsha River–Three Gorges cascade reservoirs as an example, the calculation is carried out and compared with other algorithms. The results show that the FPLSA performed better than the other algorithms in all of the indices measured which means it has stronger optimization ability. Under the premise of satisfying the constraints of cascade reservoirs, an approximate optimal solution could be found to provide an effective output strategy for cascade reservoir scheduling.

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“…The experimental results show that the improved algorithm has better performance. Donyaii et al [21] improved WOA for water resource management and reservoir operation and analyzed water resource management problems using WOA. Bozorgi and Yazdani [22] improved WOA by combining WOA with differential evolution (DE) to solve the premature convergence problem of WOA and verified the performance of the improved algorithm through experiments.…”

Section: Introductionmentioning

confidence: 99%

Position Deployment Optimization of Maneuvering Conventional Missile Based on Improved Whale Optimization Algorithm

Zhang

Zhao

et al. 2022

International Journal of Aerospace Engineering

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To reasonably allocate mobile conventional missile battle positions and improve the survivability and combat effectiveness of the missile weapon system, a missile position deployment optimization design model based on Mixed-Integer Nonlinear Programming (MINLP) is established. First, for the multilevel position network, an optimization model with the goal of maximizing the viability is established, and a two-stage solution method is proposed. Second, the whale optimization algorithm (WOA) is improved, and the convergence factor which changes nonlinearly with the number of evolution is introduced to coordinate the local development and global search ability of the algorithm. The diversity mutation operation is carried out on the optimal individual to reduce the probability of premature convergence of the algorithm, and the improved whale algorithm is used to solve the optimization model. Finally, the performance of the improved algorithm is verified by example analysis and simulation experiments, which provides a reference for the deployment mode of mobile missile positions.

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A Novel Approach to Supply the Water Reservoir Demand Based on a Hybrid Whale Optimization Algorithm

Cited by 14 publications

References 41 publications

Investigating dam reservoir operation optimization using metaheuristic algorithms

Investigating dam reservoir operation optimization using metaheuristic algorithms

Optimization of Cascade Reservoir Operation for Power Generation, Based on an Improved Lightning Search Algorithm

Position Deployment Optimization of Maneuvering Conventional Missile Based on Improved Whale Optimization Algorithm

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