Optimum Operation of Reservoir Using the Genetic Algorithm and Particle Swarm Optimization (Case Study: Alavian Dam)

In this study, for the purpose of optimum utilization of water reserved in Alavian dam, two meta-heuristic methods (particle swarm optimization and genetic algorithm) were used. The performances of the methods were evaluated using the reliability, vulnerability and sustainability indices. Objective function was defined in terms of minimization of the total sum of squares of the ratios of deficits to the maximum demand during the time period of 1998 to 2013. The output of the selected algorithm was compared with that of the standard operation policy method. The results showed that particle swarm optimization algorithm having the reliability, vulnerability and sustainability indices of 80.11, 84.91 and 55.89 percentages was more suitable than genetic algorithm having the mentioned indices equal to 78.94, 75.91 and 46.2 percentages, respectively. According to the calculated indices for standard operation policy in which the reliability, vulnerability and sustainability indices were equal to 70.83, 98.92 and 8.24 percentages, it could be concluded that the particle swarm optimization algorithm was more suitable than the genetic algorithm.