摘要
针对蚁群算法不太适用于连续优化问题,且在搜索过程中容易陷入局部极值的缺点,提出了一种快速全局优化的改进蚁群算法,该算法同时采用在最好解蚂蚁领域内进行搜索及将本次循环得到的最优解作为起始解的搜索方式,以扩大其搜索范围,避免其陷入局部最优。通过对3个典型函数优化问题进行测试并与其他优化算法进行比较,结果表明该改进算法不仅能应用于对连续对象的优化,同时具有良好的全局优化性能,收敛速率快,寻优精度高。
Aim to the disadvantages that ant colony optimization is not applied to continuous optimization problems and easy to get into local optimum, a fast global ant colony algorithm is proposed. In this algorithm the searching way that searches near the best solution and makes the best solution as the initial solution is adopted in order to widen searching scope to avoid getting into local optimum, and then it is used to test some typ- ical functions. Comparing with other optimizations, the testing result indicates that the improved algorithm is not only applied to continuous optimization problems, but also has fast global optimization, fast searching rate and high optimizing precision.
出处
《青岛科技大学学报（自然科学版）》
CAS
2009年第2期179-182,共4页
Journal of Qingdao University of Science and Technology:Natural Science Edition
基金
辽宁创新团队项目资助(2006T089)
关键词
蚁群算法
全局优化
连续优化
ant colony algorithm
global optimization
continuous optimization
