摘要
实际应用中经常用人工智能算法如遗传算法求解TSP等一类NP难题,针对原有的遗传算法在初始化种群随机性的缺陷以及在产生子代过程中无法保存最优个体的问题,给出基于贪心算法的种群初始化和交叉变异后最优个体保存算法相结合的改进遗传算法,并在VC++平台上对该算法的实现过程进行动态演示。
People always use artificial intelligence algorithms such as genetic algorithm to solve a class of NP prolems like TSP. For the original algorithm has the randomness of defects in initialization of population and can＇t save the best individual in the generating offspring, presents an improved genetic algorithm which based on greedy algorithm to initialize the population and preserve the best individual after crossover and mutation, and presents the realization process of the algorithm on VC＋＋ platform.
关键词
遗传算法
TSP问题
贪心算法
最优保存算法
Genetic Algorithm
TSP
Greedy Algorithm
Optimal Preservation Algorithm
