Sabbaghpour, Saman, Naghashzadehgan, Mohammad, Javaherdeh, Kourosh, and Haddad, Omid Bozorg
Subjects
*ANIMAL sexual behavior, *HONEYBEES, *ALGORITHMS, *APIS (Insects)
Abstract
In this paper a new meta-heuristic approach based on the nature of honey bees mating has been used for the calibration of a real city in the north of Iran named Langarud. This city has a population of nearly 68,000 people and about 43,000 water consumers. Langarud's area is about 900 km². The method was used to determine the Hazen-Williams roughness factor of the main pipes of the town and a correction factor for the nodal demands in the main nodes of the network. [ABSTRACT FROM AUTHOR]
Heuristic search techniques are highly flexible, though they represent computationally intensive optimization methods that may require thousands of evaluations of expensive objective functions. This paper integrates MODSIM, a generalized river basin network flow model, a particle swarm optimization (PSO) algorithm and artificial neural networks into a modeling framework for optimum water allocations at basin scale. MODSIM is called in the PSO model to simulate a river basin system operation and to evaluate the fitness of each set of selected design and operational variables with respect to the model's objective function, which is the minimization of the system's design and operational cost. Since the direct incorporation of MODSIM into a PSO algorithm is computationally prohibitive, an ANN model as a meta-model is trained to approximate the MODSIM modeling tool. The resulting model is used in the problem of optimal design and operation of the upstream Sirvan river basin in Iran as a case study. The computational efficiency of the model makes it possible to analyze the model performance through changing its parameters so that better solutions are obtained compared to those of the original PSO-MODSIM model. [ABSTRACT FROM AUTHOR]