Notice of RetractionApplication of multi-objective evolutionary algorithm to cascade reservoirs operation

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

In this paper, a multi-objective evolutionary algorithm, the non-dominated sorting genetic algorithm (NSGA-II), is applied to examine the operations of four cascade reservoirs system in the upper Wujiang River, Guizhou Province of China. The Optimization model is established with two objects, which are the maximal generation of and the firm power in certain probability. The NSGA-II is applied to simulate optimal operating strategies based on a 10 year data set. Two representative algorithms, dynamic programming with successive approximation (SADP) and discrete differential dynamic programming, are also applied to evaluate simulation performance. The result demonstrates that both the annual generation and the firm power of cascade system, derived from NSGA-II, are superior to the traditional strategy and the other two algorithms. It indicated that NSGA-II exhibits obvious advantage on solution of complex multi-variable and multi-objective problems on comparison with other traditional optimization algorithms.