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用于连续函数优化的蚁群算法
引用本文:陈烨.用于连续函数优化的蚁群算法[J].四川大学学报(工程科学版),2004,36(6):117-120.
作者姓名:陈烨
作者单位:四川大学,电气信息学院,四川,成都,610065
摘    要:为了用蚁群算法来解决连续优化问题,该算法将函数优化问题中生成解的过程转化为蚁群每前进一步就选择一个十进制数字并以此来生成一个十进制串的过程。与普通蚁群算法相同,蚁群在选择数字的过程中将一定量的信息记录在每条选择的路径上以改变下一次蚁群选择各个数字的概率。实验数据表明,文中的函数优化算法能比遗传算法以及其他用于连续优化的蚁群算法更快地找到更好的解。这种算法为蚁群算法求解连续优化问题提供了一种新的方法。

关 键 词:蚁群算法  旅行商问题  连续函数优化
文章编号:1009-3087(2004)06-0117-04

Ant Colony System for Continuous Function Optimization
CHEN Ye.Ant Colony System for Continuous Function Optimization[J].Journal of Sichuan University (Engineering Science Edition),2004,36(6):117-120.
Authors:CHEN Ye
Abstract:Based on Ant Colony System,a new algorithm for continuous function optimization is propose.Each ant makes a selection from ten decimal numbers whenever it takes a step in this algorithm. And in this way a solution for the function optimization problem can be built. The same as general Ant Colony System, the ants will change the information left on their paths, so that the probability that an ant chooses a number in a step next time can be changed to lead the ant to a better path. The experimental result shows that this new algorithm can find a better solution for function optimization problem than genetic algorithms and other ant colony system for continuous optimization. This new algorithm presents a new way to solve continuous optimization problems.
Keywords:Ant Colony System  traveling salesman problem  continuous function optimization
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