Optimal reservoir operation has become a challenging problem due to streamflow uncertainties. Frameworks for optimal reservoir operation play a vital role in the management of water resources. Effective and judicious utilization of water from reservoirs helps to manage water deficit periods. The main objective in reservoir optimization is to design operating rules that can be used to derive real-time decisions on reservoir release. In this study a metaheuristic optimization algorithm, Parametric Elitist Cuckoo Search Algorithm (PECSA) based on basic Cuckoo Search Algorithm, has been applied for developing optimal operation decisions for Ravishankar Sagar reservoir in Mahanadi Reservoir Project complex, India. To evaluate the performance of the improved PECSA, the results obtained by this method has been compared with another heuristic method Time Variant Elitist Mutation Particle Swarm Optimization (TVEMPSO) algorithm and also with the standard CSA and PSO methods. PECSA improves system operation and has outperformed other methods in terms of achieving faster convergence rate. Besides, PECSA has also shown minor variations in optimal pattern of release policies with those obtained using the standard CSA. Finally, implication of the results and suggestion for further research are discussed.
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