Papers by Author: Shu Zhi Nie

Abstract: In this paper, According to the collaborative manufacturing resources optimization deployment problems, designed subsection crossover and subsection mutation based on process code, adopted fitness scaling method and ranking method to select operators, proposed an improved genetic algorithm based on DNA computation for solving the resources optimization deployment problems, so that the offspring are better able to inherit the good features of parent. Through simulation, tested the designed algorithm performance; by comparing with conventional genetic algorithm test results, it proved the validity of the designed algorithm.

Abstract: In this paper, built mathematical model on Flow Shop scheduling, put forward a RNA genetic algorithm based on DNA computing to solve the Flow Shop scheduling problems. Adopt RNA four digit system encoding method based on DNA computing and RNA computing operator in genetic algorithm. It resolved the encoding scheme and convergence problem which exists in the conventional genetic algorithm. Under some constraint conditions, this genetic algorithm got simulated. Simulation results showed that this algorithm has a better optimum searching and seeking abilities, made the scheduling results comparatively reasonable and expanded the application of DNA computing.