Crow algorithm for irrigation management: A case study
Document Type
Article
Publication Date
2-1-2020
Abstract
This study employed a new evolutionary algorithm namely, the crow algorithm (CA), to optimize reservoir operation and minimize irrigation water deficit. Comprehensive analysis have been carried out between the proposed CA algorithm and other algorithms such as Prticle Swarm optimization (PSO), Shark Algorithm (SA), Genetic Algorithm (GA), and Weed Algorithm (WA). In addition, in order to select the optimal optimization algorithm among all of the investigated ones, a Multi-Criteria Decision model has been utilized. The time of computation was 45 s for CA but was 65, 50, 78, and 99 s for SA, WA, PSO, and GA, respectively. The CA exhibited greater volumetric reliability and a lower vulnerability index over the other examined algorithms. Furthermore, the Root Mean Square Error (RMSE) between demand and water release was 1.11 x 10(6) m(3) for CA compared to 2.14 x 10(6) m(3), 3.33 x 10(6) m(3), 3.45 x 10(6) m(3), and 3.78 x 10(6) m(3) for SA, WA, PSO, and GA, respectively. Using a multi-criteria decision model based on different indices, including the vulnerability index, resiliency index and volumetric reliability index, CA was ranked first.
Keywords
Crow algorithm, Water resources management, Reservoir operation, Irrigation management
Divisions
sch_civ
Funders
University of Malaya Research,GPF082A-2018,Universiti Malaya
Publication Title
Water Resources Management
Volume
34
Issue
3
Publisher
Springer Verlag
Publisher Location
VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS