Abstract: Ant colony algorithm is an optimized model which bases on the principle of swarm intelligence, it is used to solve the problem of optimization. We use ant colony algorithm to find the optimization solution of the set-covering problems, while set-covering is one of the most popular application in NP-complete problem, it has important application, such as in the field of mode identity, machine learning and so on. The contrast of several algorithm proves that using the ant colony algorithm to solve the problem of set covering is efficiency and feasible.

摘要： 蚁群算法是一种基于群体智能原理的优化模型，用于解决组合优化问题。集合覆盖问题是NP完全问题中应用面最广的问题之一,它在模式识别,机器学习等领域中具有重要的应用。本文以SCHF[1]启发函数作为启发信息，用蚁群算法求得集合覆盖问题的优化解。通过几种算法的仿真结果对照表明，用蚁群算法求解集合覆盖问题是有效的，蚁群算法得到的解是比较理想的。