Performance evaluation of elitist-mutated multi-objective particle swarm optimization for integrated water resources management

M. Janga Reddy Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India D. Nagesh Kumar (corresponding author) Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India E-mail: [email protected] Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting goals, which often leads to multi-objective optimization. In aid of effective decision-making to the water managers, apart from developing effective multiobjective mathematical models, there is a greater necessity of providing efficient Pareto optimal solutions to the real world problems. This study proposes a swarm-intelligence-based multiobjective technique, namely the elitist-mutated multi-objective particle swarm optimization technique (EM-MOPSO), for arriving at efficient Pareto optimal solutions to the multi-objective water resource management problems. The EM-MOPSO technique is applied to a case study of the multi-objective reservoir operation problem. The model performance is evaluated by comparing with results of a non-dominated sorting genetic algorithm (NSGA-II) model, and it is found that the EM-MOPSO method results in better performance. The developed method can be used as an effective aid for multi-objective decision-making in integrated water resource management.