计算机与数字工程Issue(11)：2004-2013,10.DOI:10.3969/j.issn1672-9722.2014.11.004
蚁群算法求解旅行商问题综述*
Review of Ant Colony Algorithm for Solving Traveling Salesman Problem
摘要
Abstract
Ant colony optimization(ACO) is a meta‐heuristic random search technique to solve combination optimization problems effectively .Traveling Salesman Problem(TSP) is a typical combination optimization problem ,which is easy to be described and hard to be solved .After describing the basic principle of three classical ant colony algorithm for solving the traveling salesman problem ,current development situations of ant colony algorithm are emphatically analyzed .Five main de‐velopment directions of ant colony algorithm are summarized ,including ,local optimization algorithm based ant colony algo‐rithm ,the improvement of the pheromone update method ,the combination of ant colony algorithm and other algorithm ,opti‐mize parameter of ant colony algorithm and parallel ant colony algorithm .And these five development directions have the trend of integration .关键词
旅行商问题/蚁群算法/信息素/组合优化/融合Key words
traveling salesman problem/ant colony algorithm/pheromone/combinatorial optimization/integration分类
信息技术与安全科学引用本文复制引用
宗德才,王康康,丁勇..蚁群算法求解旅行商问题综述*[J].计算机与数字工程,2014,(11):2004-2013,10.基金项目
江苏省高校自然科学基础研究项目（编号13KJB110006）资助。 （）
