A hybrid Goal Programming method and Adaptive Neural-Fuzzy Inference System for Optimal Operation of a Multi-Objective Two- Reservoir System

Optimization of reservoirs operation is one of the most important tasks in the field of water resources management. In fact, vital requirement for beneficial use of water and energy resources clear the necessity of doing integrated planning and right operation of dams. recently, research has been made focusing on a shift from traditional single objective models to multi–objective models for the planning of multiple reservoir systems in a river basin. In this study the three objectives of meeting irrigation and environmental demand, flood control and recreation (sometimes in conflict with each other) are referred to for a two reservoir system by Goal Programming. Within this framework, the mathematical model of two reservoirs system in Sefidrud watershed (Northern Iran) with the three objectives is formulated and the system parameters and decision variables are defined. The problem involves finding desired water releases from each reservoir in the system in order to satisfy the multiple objectives. With comparing results of optimization models of this study, the model with the higher reliability indices was chosen as the best model. Due to the considerable advantages of linguistic rules in better inferring and interpreting the systems, an adaptive neural based fuzzy inference system (ANFIS) approach is used to consider uncertainties and to achieve a general method for multipurpose multi reservoir systems. The results of the Adaptive Neural Fuzzy Inference System (ANFIS) models shows that they can be applied successfully to provide high accuracy for the management of the reservoir systems.