Optimizing Reservoirs Exploitation with A New Crow Search Algorithm Based on a Multi-Criteria Decision-Making Model

Mousavi, Sayed‐Farhad; Vaziri, Hamidreza; Karami, Hojat; Hadiani, O.

doi:10.29252/jstnar.22.1.279

Cited by 7 publications

(3 citation statements)

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“…A case study by Mousavi et al [21] using the crow algorithm for extracting rule curves to manage irrigation on the basis of the potential of crows for finding and hiding foods showed significant decreases in the vulnerability index.…”

Section: Review Of the Literaturementioning

confidence: 99%

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

Donyaii

Sarraf

Ahmadi

2020

Shock and Vibration

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Managing water resources requires the optimum operation of dam reservoirs. To satisfy the downstream water demand in the operational optimization of Boostan dam reservoir, the improved whale optimization algorithm (IWOA) performance was compared in the present study with that of its constituents (i.e., the whale optimization and differential evolution) based on GAMS nonlinear programming results. The model evaluative indicators and an objective function were used to select the optimal algorithm. The findings suggested that IWOA resulted in the lowest computational duration and fastest convergence rate compared to the other algorithms. Additionally, the average water demand and discharge volume of IWOA were 3.21 × 106 m3 and 3.03 × 106 m3, respectively. In contrast, the other algorithms yielded lower water release volumes. IWOA enhanced the WOA performance by 21.7% through reducing the variation coefficient by 78% in optimizing the objective function. The water demand was therefore more effectively satisfied by the IWOA compared to the other algorithms. Furthermore, the IWOA resulted in a lower amount of errors. The hybrid algorithm performance increased in terms of all the evaluative indicators. Developing multicriteria decision-making models using TOPSIS and the Shannon entropy also suggested the IWOA excels the other algorithms in optimizing the reservoir operational problem.

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Section: Review Of the Literaturementioning

confidence: 99%

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

Donyaii

Sarraf

Ahmadi

2020

Shock and Vibration

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“…The water released from the reservoirs was considered to be a decision variable. The results indicated that this new algorithm, which is based on the social behavior of monkeys, can obtain a global solution with less computation time than the PSOA and GA. For a case study in Iran, Mousvai et al [11] applied the crow algorithm (CA) for irrigation management. This algorithm acts based on the behavior of crows attempting to find food.…”

Section: Introductionmentioning

confidence: 99%

Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies

et al. 2019

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One of the most important issues in the field of water resource management is the optimal utilization of dam reservoirs. In the current study, the optimal utilization of the Aydoghmoush Dam Reservoir is examined based on a hybrid of the bat algorithm (BA) and particle swarm optimization algorithm (PSOA) by increasing the convergence rate of the new hybrid algorithm (HA) without being trapped in the local optima. The main goal of the study was to reduce irrigation deficiencies downstream of this reservoir. The results showed that the HA reduced the computational time and increased the convergence rate. The average downstream irrigation demand over a 10-year period (1991–2000) was 25.12 × 106 m3, while the amount of water release based on the HA was 24.48 × 106 m3. Therefore, the HA was able to meet the irrigation demands better than some other evolutionary algorithms. Moreover, lower indices of root mean square error (RMSE) and mean absolute error (MAE) were obtained for the HA. In addition, a multicriteria decision-making model based on the vulnerability, reliability, and reversibility indices and the objective function performed better with the new HA than with the BA, PSOA, genetic algorithm (GA), and shark algorithm (SA) in terms of providing for downstream irrigation demands.

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“…Mousavi et al [22] applied the crow algorithm for the extraction of rule curves for the irrigation management for a case study. The algorithm acted based on ability of crows for the finding and hiding of food.…”

Section: Introductionmentioning

confidence: 99%

Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm

Ehteram

Singh

Karami

et al. 2018

Water

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Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.

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Optimizing Reservoirs Exploitation with A New Crow Search Algorithm Based on a Multi-Criteria Decision-Making Model

Cited by 7 publications

References 0 publications

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

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

Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies

Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm

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