Abstract
The scarcity of water resources is one of the most pervasive natural resource allocation problems faced by the water users and policymakers. Reservoir operation is the best solution to obtain its utmost possible performance. In the present study, the Jaya algorithm (JA) has been applied to optimize the water releases from Ukai reservoir at different dependable inflows. The model is optimized for four different dependable inflows namely 60, 65, 70, and 75%. The results from JA are compared with teaching–learning-based optimization (TLBO), particle swarm optimization (PSO), differential evolution (DE), and linear programming (LP). It was observed that JA performed better than TLBO, PSO, DE, and LP. The global optimum solution obtained using JA for 60, 65, 70, and 75% dependable inflow are 3224.620, 4023.200, 4672.800, and 5351.120, respectively in MCM. Based on the results, it is concluded that JA outperformed over TLBO, PSO, DE, and LP.
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