GAlib在遗传算法实现中的应用

Application of GAlib to the Implementation of Genetic Algorithm

遗传算法(Genetic Algorithm)是一种模拟达尔文生物进化论的随机搜索方法,被人们广泛应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。然而,编程实现遗传算法的过程非常复杂且容易引入人为的错误,进而影响相关研究的准确性。针对这一问题,讨论了基于GAlib(Genetic Algorithm Library)类库设计实现遗传算法的关键技术。最后,利用GAlib实现了遗传算法,并以解决旅行商人问题(TSP)对算法进行评估,实际效果表明,基于GAlib开发的遗传算法编程简单,可读性强,结果准确。

Genetic Algorithm （Genetic Algorithm） is a random investigation method simulating Darwin＇s biological evolution, and it is applied to the fields like combinatorial optimization, machine learning, signal processing, adaptive control and artificial life. However, the implementation process of genetic algorithm is very complicated and easily introduce error artificially, and influence the accuracy of research, for this problem, the key technology of implementing genetic algorithm based on GAlib （Genetic Algorithm Library） class library is discussed. Finally, genetic algorithm is implemented using GAlib and evaluate the algorithm by solving the traveling salesman problem（TSP）, the results shows that the genetic algorithm implemented based on GAlib is easily programming, highly readable,and results are accurate.