developing self-adaptive melody search algorithm for optimal operation of multi-reservoir systems

Operation of multi-reservoir systems is known as complicated and often large-scale optimization problems. the problems, because of broad search space, nonlinear relationships, correlation of several variables, as well as problem uncertainty, are difficult requiring powerful algorithms with specific capabilities to be solved. in the present study a self-adaptive version of melody search algorithm is presented and applied to obtain operating rule curves for multi-reservoir systems. the self-adaptive mechanism is implemented to satisfy problems constraints and perform algorithm parameters evolution going through different iterations. the research initially evaluates capability of extended algorithm using eight benchmark problems comparing other well-known metaheuristic algorithms, and verifies its effectiveness. then, the algorithm is adopted for optimal operation of a four-reservoir system located in karkheh river basin to properly meet agricultural requirements and to decrease the probability of major failures; and finally, the results are provided.