Performance Assessment of a Coupled Particle Swarm Optimization and Network Flow Programming Model for Optimum Water Allocation

Water resources allocation problems are mainly categorized in two classes of simulation and optimization. In most cases, optimization problems due to the number of variables, constraints and nonlinear feasible search space are known as a challenging subject in the literature. In this research, by co...

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Bibliographic Details
Published inWater resources management Vol. 31; no. 15; pp. 4835 - 4853
Main Authors Shourian, Mojtaba, Mousavi, S. Jamshid
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.12.2017
Springer Nature B.V
Subjects
Atmospheric Sciences
Canals
Civil Engineering
Computer simulation
Coupling
Earth and Environmental Science
Earth Sciences
Environment
Geotechnical Engineering & Applied Earth Sciences
Handling
Hydrogeology
Hydrology/Water Resources
Mathematical models
Mathematical programming
Optimization
Particle swarm optimization
Performance assessment
Performance testing
Reservoirs
Resource allocation
Resources
River basins
Rivers
Simulation
Storage
Water
Water allocation
Water resources
Simulation-optimization
Particle swarm optimization (PSO)
Water allocation planning
Network flow programming (NFP)
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Summary:Water resources allocation problems are mainly categorized in two classes of simulation and optimization. In most cases, optimization problems due to the number of variables, constraints and nonlinear feasible search space are known as a challenging subject in the literature. In this research, by coupling particle swarm optimization (PSO) algorithm and a network flow programming (NFP) based river basin simulation model, a PSO-NFP hybrid structure is constructed for optimum water allocation planning. In the PSO-NFP model, the NFP core roles as the fast inner simulation engine for finding optimum values for a large number of water discharges in the network links (rivers and canals) and nodes (reservoirs and demands) while the heuristic PSO algorithm forms the outer optimization cover to search for the optimum values of reservoirs capacities and their storage priorities. In order to assess the performance of the PSO-NFP model, three hypothetical test problems are defined, and their equivalent nonlinear mathematical programs are developed in LINGO and the results are compared. Finally, the PSO-NFP model is applied in solving a real river basin water allocation problem. Results indicate that the applied method of coupling PSO and NFP has an efficient ability for handling river basin-scale water resources optimization problems.
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-017-1781-8