Bi-objective algorithm based on NSGA-II framework to optimize reservoirs operation

Abstract Reservoir operation optimization is very important in water resource development and management. This paper focuses on the bi-objective optimization problems via proposing a novel bi-objective algorithm, called lion pride algorithm (LPA), based on the social structure of lion prides and the framework of NSGA-II. Specifically, LPA first divides the population into lion prides, then classifies the individuals into lion kings and ordinary lions based on the prides, and finally assign better fitness values to these lion kings compared to ordinary lions. Its performance in bi-objective optimization is then tested by the benchmark problems and the reservoir operation problems. Results indicate that: (1) LPA outperforms NSGA-II in convergence and diversity and runs about 2 to 4 times faster than NSGA-II for bi-objective optimization; (2) LPA has the good optimization ability for the complex problems with sharp-peak and long-tail POFs; and (3) in the reservoir operation problems of this paper, the optimization results of LPA weakly dominate 29% to 70% of those of NSGA-II, while the optimization results of NSGA-II only weakly dominate 1% to 22% of those of LPA. This study sheds a new idea for bi-objective optimization.

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