Optimal operation of reservoir for sustainable water management using multi-criteria decision-making approach

ABSTRACT Reservoir operation optimization is crucial for sustainable water resource management, but resource competition can cause conflicts, necessitating bargaining solution approaches for optimal operational schemes. In the present study, three multi-objective algorithms, Non-Dominating Sorting Genetic Algorithm II (NSGA II), Non-Dominating Sorting Genetic Algorithm III (NSGA III), and multi-objective particle swarm optimization (MOPSO), were used for optimizing Ravishankar Sagar reservoir (RSSR), Chhattisgarh, India. Furthermore, a multi-criteria decision-making analysis was carried out using the entropy method compromise programming (EMCP) approach. The results obtained showed that 83% of the demand was met using NSGA II, while NSGA III and MOPSO methods were able to meet 68 and 44% of the demand. Based on the comprehensive evaluation, it may be said that NSGA II has better potential for complex optimization problems.