Development of a Comparative Multiple Criteria Framework for Ranking Pareto Optimal Solutions of a Multiobjective Reservoir Operation Problem

Abstract

Real-world, multiobjective, reservoir optimization problems (MOOPs) usually have conflicting objective functions. Multiobjective evolutionary algorithms (MOEAs) have been applied to solve multiobjective optimization problems. Given that MOOP solutions cannot minimize or maximize all objectives simultaneously, it is difficult to determine Pareto optimal solutions (POS). This paper presents a comparative multimethodological framework that implements five multicriteria decision-making methods (MCDMs) to determine POS for a single-reservoir system with three objective functions. The Borda technique was successfully employed to rank the MCDMs’ solutions. The reservoir system’s release, storage, and generated hydropower were optimized based on the best-ranked MCDMs’ solutions. This paper’s methodology introduces practical computational framework for making robust decisions in complex reservoir operation problems and demonstrates its applicability.