APPLICATIONS OF GENETIC ALGORITHMS IN DYNAMIC PARAMETER RECOGNITION OF CRYSTALLINE PROCESS

Genetic algorithms comprise a family of stochastic optimization strategies which are often applied to solve complex optimization problems. The population based search,recombination and mutation distinguish the genetic algorithms from other optimization techniques. In this paper, genetic algorithms are employed to recognize the dynamic parameters of crystalline process in supersaturated solutions of Li 2O\53B 2O 3 H 2O system. The recognized parameters are crystalline reaction rate, thermodynamic equilibrium concentration and apparent reaction order. The factors, including population size, recombination rate and mutation rate, which influence the convergence of genetic algorithms have been discussed. The results show that variations of these parameters must not always improve the trial solutions. In addition, the finding of high accuracy crystalline dynamic equation shows that genetic algorithm can be used as a robust technique for parameter recognition.