蚁群优化算法在求解随机组合优化问题中的应用综述*

不确定条件下的优化问题更贴近真实世界环境，因而日益受到广泛关注。综述了蚁群优化在求解一组不确定条件下的组合优化问题，即随机组合优化问题方面的应用。首先介绍了不确定条件下组合优化问题的概念分类模型，给出了随机组合优化问题的一般定义；然后指出了其与求解传统确定性组合优化问题的不同之处，即目标函数的计算存在不确定性，并详细论述了目前解决方法的进展；最后分析了该领域值得重点关注的几个研究方向，并对其未来发展进行了展望。

Survey on ant colony optimization algorithms for stochastic combinatorial optimization

The optimization problem under uncertainty because of its closer to the real world environment, thus have become a growing reasearch area recently. This paper thoroughly reviewed ant colony optimization algorithms, and their applications to the class of stochastic combinatorial optimization problems under uncertainty conditions. Firstly, introduced the conceptual classification model for combinatorial problems under uncertainty conditions and a general definition for the stochastic combinatorial optimization problem. Then, pointed out the main difference between stochastic combinatorial optimization problem and deterministic combinatorial optimization problem, that was the computation of the objective function under uncertainty, and then summarized the current solutions for solvins this problem. Finally, proposed several possible research directions and the expectations of the development in this area.