Extraction of Multicrop Planning Rules in a Reservoir System: Application of Evolutionary Algorithms
Publication: Journal of Irrigation and Drainage Engineering
Volume 139, Issue 6
Abstract
Multicropping is the practice of growing two or more crops in the same space during a single growing season. Planning rules are mathematical equations that use previous experiences of a water resource system to balance the system’s water supply and demand, and calculate multicrop areas in various periods. In this paper, linear and nonlinear planning rules are developed for optimal multicrop irrigation areas associated with reservoir operation policies in a reservoir-irrigation system. Reservoir operations are related to water allocations to each irrigated area by considering inflow and storage volume of the reservoir as the water supply in a monthly operation period. Evolutionary algorithms (EAs) can determine optimal multicropping patterns planning rules by considering various mathematical patterns. In this paper, three EAs, namely, (1) genetic algorithm (GA), (2) particle swarm optimization (PSO), and (3) shuffled frog leaping algorithm (SFLA) are employed and compared to maximize the total net benefit of the water resource system by supplying irrigation water for a proposed multicropping pattern over the planning horizon. Results show that the SFLA achieves the best solution, with the maximum value of the objective function in both linear and nonlinear planning rules compared to the GA and PSO. Moreover, the best yield of nonlinear rules is 45.52% better (higher) than that obtained by linear rules.
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Published In
Journal of Irrigation and Drainage Engineering
Volume 139 • Issue 6 • June 2013
Pages: 490 - 498
Copyright
© 2013 American Society of Civil Engineers.
History
Received: Aug 18, 2012
Accepted: Dec 14, 2012
Published online: Dec 17, 2012
Published in print: Jun 1, 2013
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