Improved Chaos Genetic Algorithm And Its Application In Artillery Firepower Distribution

Since the advent of genetic algorithm,people have carried out in-depth study on it and solve the nonlinear problems constantly.In the face of simple linear or nonlinear problems,genetic algorithm has a unique advantage compared with other optimization algorithm.However,when the problem is a complicated nonlinear problem or multi peak problem,the lack of ability that adapts to the problems is revealed gradually.Therefore,many scholars tried to improve or combine the genetic algorithm with other algorithms on it,and made good achievements.The chaos genetic algorithm is one of the improved method.In the most of the current literature,there are basically integrate the chaos sequence into the initial population of genetic algorithm and the algorithm ends proportionally adding chaotic disturbance,this way can integrate the ergodicity of chaos and randomness well in the genetic algorithm,but the genetic algorithm itself has lots of room for improvement.So,this thesis proposes that this degree of improvement is still not perfect,so this thesis presents an improved chaos genetic algorithm.The biggest highlight of this thesis is to propose a method of selecting chaotic effects,that is,the choice of chaos.Specifically,it is the use of small disturbance added to the same individual choice,which has little difference,but still has small gap with the original value.This avoids the defects of "recent breeding",but also much loss of original good genes.In addition,on the basis of previous research,this thesis chooses the Tent chaotic map,but unlike some literature that chaos coefficient is 1.5,and through the comparative analysis,the chaotic coefficient is 1.9999 and this figure is meant to more close to 2.The design of adaptive crossover operator,mutation operator and the sensibility of the fitness function,the genetic algorithm makes in the operation process,which make the various parameters using algorithm more reasonable.Finally,the simulation results of common mathematical functions design shows that between improved chaotic genetic algorithm with the reference of chaos genetic algorithm and the genetic algorithm,the designed algorithm is more efficient.Because there are few people who have tried to use the chaos genetic algorithm to solve the optimal allocation problem in the artillery fire distribution.So this thesis choose to use the improved algorithm proposed in this thesis to simulate it with the software Matlab,and finally come up with the best distribution scheme.This also provides a new option for firepower distribution.