蚁群算法研究与应用的新进展  

New progress of the ant colony algorithm in research and applications

作　　者：覃远年[1] 梁仲华 QIN Yuan-nian;LIANG Zhong-hua(School of Information and Communication,Guilin University of Electronic Technology,Guilin 541004,China)

机构地区：[1]桂林电子科技大学信息与通信学院,广西桂林541004

出　　处：《计算机工程与科学》2019年第1期173-184,共12页Computer Engineering & Science

基　　金：国家自然科学基金(61261035)

摘　　要：蚁群算法是一种源于大自然生物界的仿生进化算法,具有自组织性、正反馈性、较强的鲁棒性和分布式计算等特性,且易于与其它算法相结合,在众多的复杂组合优化领域中有着广阔的应用前景。首先对蚁群算法的理论及其重要参数进行了阐述,继而分析了其在参数优化和智能融合方面的改进与应用;然后对其在车间作业调度问题、车辆路径问题、图像处理、电力系统优化等领域的应用进展进行了综述;最后对其理论研究和应用领域可能存在的问题及对策进行了探讨和展望。The ant colony algorithm is a bionic evolutionary algorithm derived from the natural biological world. It has the characteristics of self-organization, positive feedback, strong robustness, and distributed computing, and it is easy to combine with other algorithms. it is therefore of great applied value in the complex combinatorial optimization field. We firstly introduce the theory of the ant colony algorithm and its important parameters. Then we analyze the improvement and applications in parameter optimization and intelligent fusion. Thirdly, we summarize the progress of applications in job-shop scheduling problem, vehicle routing problem, image processing and electric power system optimization. Finally, we discuss the potential problems in research work in theory and application domain, as well as some possible countermeasures.

关 键 词：蚁群算法 复杂组合优化 算法改进 应用进展 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]