Many-objective reservoir operation optimization using NSGA-III and decision-support analysis: a sustainable management framework for the Indira Sagar Reservoir, India

Abstract Efficient reservoir operation requires simultaneous consideration of competing goals related to hydropower generation, water-supply reliability, flood management, and storage regulation. However, deriving balanced operating policies becomes increasingly complex when several conflicting objectives are considered concurrently. This study develops a many-objective optimization framework for the Indira Sagar Reservoir, India, considering four objectives: maximization of hydropower generation and minimization of water deficit, spill losses, and storage deviation. The reservoir operation model integrates hydrological inputs, demand characteristics, operational constraints, and reservoir continuity relationships. Five metaheuristic algorithms Non-dominated Sorting Genetic Algorithm II (NSGA-II), Non-dominated Sorting Genetic Algorithm III (NSGA-III), Multi-Objective Particle Swarm Optimization (MOPSO), Multi-Objective Ant Colony Optimization (MOACO), and Multi-Objective Teaching–Learning-Based Optimization (MOTLBO were comparatively evaluated using Hypervolume (HV), Inverted Generational Distance (IGD), and computational performance indicators. NSGA-III achieved an HV of 0.9234 and an IGD of 0.0338, demonstrating effective convergence and diversity for the evaluated solutions. Pareto analysis revealed distinct trade-offs among energy generation, water shortage, spill, and storage regulation. The Weighted Sum Method (WSM) identified Solution S10 as the selected compromise policy, providing 4106.8 GWh/year hydropower generation, 352.9 MCM/year water deficit, and 92.3% reliability. Scenario-based evaluation under normal, flood, and drought conditions further demonstrated variations in policy performance across hydrological regimes. The framework provides a structured decision-support approach for strategic reservoir operation and facilitates transparent evaluation of trade-offs among competing water-resource objectives.