论文标题
基于GPGPU的平行蚂蚁菌落优化的概述和应用
Overview and Applications of GPGPU Based Parallel Ant Colony Optimization
论文作者
论文摘要
蚂蚁菌落优化算法是基于蚂蚁行为的宏伟启发式技术。并行计算是在可相当的执行时间中实现所需结果的一种手段。蚂蚁菌落优化的并行化用于解决大型和复杂的问题。本文讨论了对蚂蚁菌落优化及其各种应用的不同平行化方法的评论。事实证明，平行的蚂蚁菌落优化是一种成功约束问题（例如路由，调度，时间表等）的成功方法。蚂蚁菌落优化的并行化缩短了执行时间，增加了问题的大小，等等。
Ant Colony Optimization algorithm is a magnificent heuristics technique based on the behavior of ants. Parallel computing is a means to achieve the desired results in commensurable execution time. Parallelization of Ant Colony Optimization is utilized to solve large and complex problems. This paper discusses a review of different parallelization approaches for Ant Colony Optimization and its various applications. Parallel Ant Colony Optimization has proved to be a successful approach for highly constrained problems such as routing, scheduling, timetabling, etc. Parallelization of Ant Colony Optimization reduces the execution time, increases the size of the problem, etc.
