蚁群最优化--模型、算法及应用综述

蚁群系统所具有的分布式组织模型对解决复杂组合优化问题、分布控制问题提供了很好的思路，因此对蚁群系统行为及其自组织能力的研究已经引起了许多研究者的兴趣．蚁群最优化(ant colony optimization，ACO)是蚁群系统的一个重要研究领域，新模型、新方法、新应用不断出现、论文对ACO的仿生学机理进行了描述．综合ACO在不同种类的组合优化问题上的应用，建立了ACO的一般化模型．对ACO的典型实现过程和关键实现要素进行了分析，指出了不同ACO算法的本质区别、结合旅行商问题、二次指派问题以及网络路由问题等典型组合优化问题，概述了ACO在静态组合最优化和动态组合优化问题中的应用．最后讨论了ACO在建模、实现以及理论研究等方面的未来方向。

Ant colony optimization review:Modelling,algorithms and applications

The study on ant colonies behavior and their self_organizing capacities has been interesting for many researchers because it provides models of distributed organization which are useful to solve difficult combinatorial optimization problems (COPs) and distributed control problems. Ant colony optimization (ACO) is one important research area of ant colonies, and new models, methods and applications are presented increasingly. The bionics mechanism of ACO is described in this paper. Synthesizing various applications of ACO to different COPs, a general ACO model is presented. The typical implementation process and key elements of ACO are analyzed, and essential differences among different ACO algorithms are observed. The applications of ACO to static and dynamic COPs, such as traveling salesman problem, quadratic assignment problem, network routing problem are reviewed. The developing tendency on modeling, implementing and theory research is discussed.