DNA accelerating evolutionary algorithm and its application in the parameter optimization of Muskingum routing model

In order to reduce the computational load and improve the computational accuracy for parameter optimization of Muskingum routing model, a new algorithm, DNA accelerating evolutionary algorithm (DNAAEA) is proposed. With the shrinking of searching range, the method gradually directs to optimal result with the excellent individuals obtained by DNA evolutionary algorithm. Its global convergence is analyzed. Its efficiency is verified by application of Muskingum routing model. Compared with standard binary-encoded genetic algorithm (SGA), real-valued accelerating genetic algorithm (RAGA), least residual square algorithm (LRSM) and the test method (TM), DNAAEA has higher precision and rapider convergent speed. It is good for the global optimization in the practical water environmental models.