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Showing 4 results for Optimization Model
Development of Hydraulic-Economic Simulation-Optimization Model for the Design of Basin Irrigation
M. Akbari,
Volume 24, Issue 4 (11-2020)
Abstract
The objective of this research was the development of a hydraulic-economic simulation-optimization model for the design of basin irrigation. This model performed hydraulic simulation (design of basin irrigation), using Volume Balance model, economic simulation through calculating sum of four seasonal costs and optimization using NSGAII multi-objective meta-heuristic algorithm. For programming, MATLAB programming software was applied. The optimizations of functional, multi-dimensional, static, constraint, continuous, multi-objective and meta-heuristic were applied for the optimization of the objective functions. Decision variables selected from simulation inputs were calculated in such a way that the  hydraulic objective function (minimizing linear combination of seven performance indicators) and economic objective function (total seasonal cost based on sum of water cost, labor cost, basin preparing cost and channel drilling cost) were minimized. Data of one the experimental field was used for the purpose of simulation. After initial simulation, optimization of the experimental field was done using NSGAII multi-objective meta-heuristic algorithm with tuned parameters. Optimization using the suggested model shoed the decrease (improvement) of objective functions rather than initial simulation performance. As a result, the suggested model could be regarded as is a specialized tool for basin irrigation, showing a good performance, despite its simplicity.

Two-Objective Simulation-Optimization Model for Cropping Pattern and Water Allocation in Semnan Plain
M. Ghodspour, M. Sarai Tabrizi, A. Saremi, H. Kardan Moghadam, M. Akbari,
Volume 25, Issue 3 (12-2021)
Abstract
The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of ​​5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.

Maximizing Economic Water Productivity Index in Agriculture in Different Levels of Irrigation
A. Mehrabi, M. Heidar Pour, H. R. Safavi,
Volume 25, Issue 4 (12-2021)
Abstract
Designing an optimal crop pattern and on-time water allocation of water resources along with deficit irrigation are among the optimal solutions to maximize the water economic efficiency index. In this paper, the simultaneous optimization of crop pattern and water allocation are discussed using the deficit irrigation method. The study area is located west of the Qazvin plain irrigation network. The six different levels of percentage reduction of irrigation rate (0, 0 to 10, 0 to 20, 0 to 30, 0 to 40, and 0 to 50%) in three climatic conditions consist of dry, normal, and wet years were compared. The best irrigation scenario was selected for each year, and the results were compared with the existing crop pattern of the same year. The new crop pattern included the main crops of the region and the addition of rapeseed. The objective was to reach the maximum net benefit per unit volume of water by considering the maximum extraction of monthly and annual surface and groundwater. The results showed that the best scenario in the dry year was maximum deficit irrigation up to 20%, in a normal year full irrigation, and a wet year maximum deficit irrigation up to 10%. The improvement of economic water productivity in a dry year was 52.2%, in a normal year 41.5%, and in a wet year is 19.6% compared to the existing crop pattern. The average percentage of annual irrigation supply increases from 64.3 to 91.7% in a dry year, from 70 to 100% in a normal year, and from 77.5 to 97.1% in a wet year. Also, the relative yield of all crops, especially wheat, alfalfa, and sugar beet significantly increases. Therefore, the gravitational search algorithm as an optimization model can be considered in selecting the suitable crop pattern and allocation of surface and groundwater resources concerning economic benefits in irrigation networks management.

Optimum Design of Furrow Irrigation: Integrating Hydrodynamic Model and Meta-Heuristic Optimization.
Amir Mahdi Bayat, Mohammad Shayannejad, Mahmood Akbari,
Volume 30, Issue 1 (3-2026)
Abstract
Mathematical models are a suitable tool for surface irrigation design. The EDOSIM model, as a surface irrigation simulation-optimization model, utilizes simulation with the volume balance model and meta-heuristic optimization. In this study, with the aim of improving the simulation of the advanced phase in the EDOSIM model, the Full Hydrodynamic model was replaced by the Volume Balance model for furrow irrigation design, leading to the development of the EDOSIM-HD model. The Saint-Venant equations were discretized using the implicit Preissmann’s finite difference scheme and transformed into a set of nonlinear equations in the form of a system of equations. The resulting system of equations was linearized using the Newton-Raphson method and solved using the Sparse matrix method. The results were compared with the SIRMOD software to validate the simulation. Using the particleswarm solver of the MATLAB software optimization toolbox, the inflow rate as a decision variable was used to optimize the hydraulic objective function consisting of efficiency, adequacy, and uniformity. The results in the experimental field showed that in the initial simulation with an inflow rate of 1.4 lps, important irrigation times, infiltration volume, performance indicators, profiles, and hydrographs showed a deep percolation loss of about 50 percent of water. Also, the results of the EDOSIM-HD model were closer to the Hydrodynamic model of the SIRMOD software than the EDOSIM model. By optimizing and increasing the optimal flow rate (1.8 lps) compared to the initial inflow rate, the advance, cut-off, depletion, and recession times were reduced, and the required infiltration time remained unchanged. The reduction in infiltration volume was also achieved by applying higher inflow rates in less time. All performance indicators also moved closer to their optimal state. Except for Tail Water Ration (TWR), which showed a slight increase of 11 percent (due to higher inflow rate), was negligible compared to the sharp 22% reduction in Depth Percolation Ratio (DPR), and 10% increase in Application Efficiency (Ea). Totally, according to the performance indicators obtained in the validation with the SIRMOD, the simulation of the EDOSIM-HD model was better than in the EDOSIM model in the advanced phase of furrow irrigation design

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