Document Type : Research Paper
Authors
Department of Water Engineering, Faculty of Agricultural Science and Engineering, Razi University, Kermanshah, Iran.
Abstract
The objective of distribution and delivery of water canal scheduling in irrigation canal networks is timely and adequate delivery of water with minimum operational stages of the head gate of supply canal in the presence of canal capacity and irrigation rotation period constraints. In this paper, two objective functions, namely, the number of gate changes and the mean discharge for two networks, were minimized by the Genetic and NSGA-II algorithms. The results showed that minimizing these two objective functions at the same time leads to fewer gate changes compared to the only mean canal discharge objective function in both algorithms. It means the mean discharge objective function cannot minimize the number of operational stages alone. Also the optimization by NSGA-II algorithm did not make a significant difference in the results in comparison with the genetic algorithm for both objective functions. However, in NSGA-II algorithm, it is not necessary to determine the weight of each of the objective functions.
Keywords
Coello Coello C., Lamont G.B., Van Veldhuizen D.A., Evolutionary algorithms for solving multi-objective problems, 2nd ed., New York, Springer (2007).
Deb K., Pratap A., Agarwal S., Meyarivan T., A fast and elitist multiobjective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation 6 (2002) 182-197.
Delaviz Y., Karami J., Shaygan M., Using NSGA-II for multi-objective optimization allocation of urban land use in order to reduce earthquake vulnerability, Journal of Geomatics Science and Technology 5 (2016) 247-264.
Goharrizi B.A., Tohidirad S., Asadi R., Using NSGA-II algorithm to solve multi-purpose location problems, Motaleate Shahri Journal 5 (2016) 15-26.
Kakouie S., and Emadi A., Optimal water delivery and distribution in AMX canal of varamin irrigation network using ACS algorithm, Iranian Water Research Journal 7 (2013) 51-58.
Konak A., Coit D.W., Smith A.E., Multi-objective optimization using genetic algorithms: A tutorial, Reliability Engineering and System Safety 91 (2006) 992–1007.
Monem M.J., and Namdarian R., Application of simulated annealing (SA) techniques for optimal water distribution in irrigation Canals, Irrigation and Drainage 54 (2005) 365–373.
Monem M.J., and Nouri M.A., Application of PSO method for optimal water delivery in irrigation networks, Iranian Journal of lrrigation and Drainage 4 (2010) 73-82.
Pawde A.W., Mathur Y.P., Kumar R., Optimal water scheduling in irrigation canal network using particle swarm optimization, Irrigation and Drainage 62 (2013) 135–144.
Qaderi Nasab F., Qaderi K., Rahnama M.B., Optimal programming for delivery and distribution of water irrigation network using evolutionary algorithms (the case study: the network irrigation at downstream of the Jiroft dam), Iranian Journal of lrrigation and Drainage 5 (2015) 830-841.
Suryavanshi A.R., and Reddy J.M., Optimal operation scheduling of irrigation distribution systems, Journal of Agricultural Water Management 11(1986) 23–30
Wardlaw R., and Bhaktikul K., Application of gentic algorithms for irrigation water scheduling, Irrigation and Drainage 53 (2004) 397-41.
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