Application In Evaluation And Decision Of Drill Based On Fuzzy Genetic Algorithm

Genetic algorithm (GA) is highly parallel and random search algorithm that simulates biological evolution mechanisms such as natural selection and "survival of the fittest". It's one of the most effective methods to solve complex problems.Theory of genetic algorithm is studied, and the affect of genetic parameters to the evolutionary process is analyzed. A fuzzy genetic algorithm is proposed to improve the performance of genetic algorithm. The crossover rate and the mutation rate are adjusted according to the evolutionary situation on-line. The difference between the maximum and the average fitness and change of the fitness in successive generations are chosen as the inputs, and fuzzy inference rules are set up by OMGA and experience. Example shows that the fuzzy genetic algorithm accelerates the evolutionary process and avoids premature convergence effectively. The fuzzy genetic algorithm also improves the optimum value.An approach for battle organizing into groups based on the above fuzzy genetic algorithm is proposed. In addition the feature of battle organizing is considered, thus a directive coding method is proposed.. Accordingly the special crossover rule and mutation rule are set up to avoid infeasible solution produced by traditional rules.The imbalance assignment problem is studied. The method transform imbalance assignment problem to balance assignment problem is proposed. The imbalance assignment problem is solved by the fuzzy genetic algorithm effectively. The good robustness of the fuzzy genetic algorithm is showed completely.