Abstract
Nowadays, due to increasing population and water shortage and competition for its consumption, especially in the agriculture, which is the largest consumer of water, proper and suitable utilization and optimal use of water resources is essential. One of the important parameters in agriculture field is water distribution network. In this research, differential evolution algorithm (DE) was used to optimize Ismail Abad water supply network. This network is pressurized network and includes 19 pipes and 18 nodes. Optimization of the network has been evaluated by developing an optimization model based on DE algorithm in MATLAB and the dynamic connection with EPANET software for network hydraulic calculation. The developing model was run for the scale factor (F), the crossover constant (Cr), initial population (N) and the number of generations (G) and was identified best adeptness for DE algorithm is 0.6, 0.5, 100 and 200 for F and Cr, N and G, respectively. The optimal solution was compared with the classical empirical method and results showed that Implementation cost of the network by DE algorithm 10.66% lower than the classical empirical method.
Highlights
Nowadays, due to increasing population and water shortage and competition for its consumption, proper and suitable utilization and optimal use of water resources is essential
In this paper the network is optimized by differential evolution algorithm (DE) and the results are compared with absolute optimum that is obtained from mixed integer linear programming (MILP) by Shahinezhad et al [30]
Conclusions show DE algorithm runtime is less than the MILP method that provides absolute optimum
Summary
Due to increasing population and water shortage and competition for its consumption, proper and suitable utilization and optimal use of water resources is essential. Shahinezhad et al [30] presented a mixed integer linear programming (MILP) model for optimization of pressurized branched irrigation networks. DE algorithm is developed to obtain the optimum pipe size and inlet pressure head that produce the least cost design of Shahinezhad et al [30] networks. The hydraulic analysis of the network is based on continuity at nodes and Hazen-Williams formula for head loss calculations by using link between Epanet and Matlab Software. The results of this investigation compared with absolute optimization are obtained by mixed integer linear programming (MILP) model that is presented by Shahinezhad et al [30]
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