An Ant Colony Optimization Algorithm Based on Dynamic Evaporation Rate Fitting
The study of swarm intelligence is more and more popular, much study have been done on swarm intelligence such as ACO (Ant Colony Optimization), and many applications also have been made in the field of combinatorial optimization. However, when solving combinatorial optimization problems, especially these problems with large scale, slow convergence and easy to fall into stagnation still restraint algorithm to be much more widely used. This paper presents the DERFACO (An ACO Algorithm Based on Dynamic Evaporation Rate Fitting) algorithm, using a mechanism of dynamic evaporation rate, which can achieve better balance between solution efficiency and solution quality, avoiding algorithm falling into local optimal. Experiments show that the DERFACO algorithm has better performance, its convergence rate increase by 12％ or more. Furthermore, the DERFACO on other classic TSP instances also shows good performance.
ant colony optimization dynamic evaporation rate data fitting
Chen Hao Liu Quan
Institute of Computer Science and Technology Soochow University Suzhou, China State Key Laboratory for Novel Software Technology Nanjing University Nanjing, China
国际会议
西安
英文
6-10
2011-05-27（万方平台首次上网日期，不代表论文的发表时间）