A Genetic Algorithm for Parameter Optimization of Streeter Phelps Model

This paper presents a new method,called genetic algorithm(GA),for the parameter optimization of Streeter-phelps model.It is comparable in performance to existing mathematical programming methods.The GA uses a population of points at a time in contrast to the single-point approach by the traditional optimization ones,and will guarantee to find the global optimum.The optimal solution by GA is no longer dependent on initial search values.The GA uses randomized operators and works on coded variables.It does not require problem derivative.