Development of Fuzzy Reservoir Operation Policies Using Genetic Algorithm

This study is focused on developing an integrated optimization-simulation model to develop the operation policies for a multi-purpose reservoir. Objective function of the optimization model is considered to be a linear function of reliability, resiliency, and vulnerability of river-reservoir systems. Genetic Algorithm (GA) is used to solve the optimization model in which the coefficients of the reservoir operation policy equations are considered as the decision variables. These coefficients are formulated in the form of fuzzy numbers to better capture the variations in releases and water demands. Due to significant variations of agricultural water demands in different months and years, a water demand time series is considered as one of the inputs of the optimization model. Zayandeh-rud River-reservoir system in central part of Iran is considered as the case study. Results of this study have shown that the developed algorithm can significantly reduce the time and costs of modeling efforts and also the run-time of the GA model, while it has also improved the overall performance of the system. Key-Words: Reliability, Resiliency, Vulnerability, Genetic Algorithm, Zayandeh-rud Reservoir, Fuzzy Regression.