Multireservoir system optimization in the Han River basin using multi-objective genetic algorithms

In this study, NSGA-II is applied to multireservoir system optimization. Here, a four-dimensional multireservoir system in the Han River basin was formulated. Two objective functions and three cases having different constraint conditions are used to achieve nondominated solutions. NSGA-II effectively determines these solutions without being subject to any user-defined penalty function, as it is applied to a multireservoir system optimization having a number of constraints (here, 246), multi-objectives, and infeasible initial solutions. Most research by multi-objective genetic algorithms only reveals a trade-off in the objective function space present, and thus the decision maker must reanalyse this trade-off relationship in order to obtain information on the decision variable. Contrastingly, this study suggests a method for identifying the best solutions among the nondominated ones by analysing the relation between objective function values and decision variables. Our conclusions demonstrated that NSGA-II performs well in multireservoir system optimization having multi-objectives.