摘要
面向服务软件的部署优化问题是典型的NP难题.本文构建了基于性能改善的软件部署优化模型,设计了一种蚁群优化算法ACO-DO进行近似最优解的快速求解.该算法通过设计基于部署优化问题的启发式、改进部署方案的构建顺序、增加局部搜索过程实现蚁群算法求解效率的提升.通过不同规模的实例实验,验证了ACO-DO算法能够取得比现有的混合整数线性规划算法、蚁群算法和遗传算法更好的性能.
The deployment optimization of service-oriented software is well known to be NP hard. In this paper,a software deployment optimization model is built for improving the performance of service-oriented software,and an Ant Colony Algorithm for Deployment Optimization（ ACO-DO） is designed to solve it so that the near-optimal solutions can be obtained quickly. The algorithm improves ant colony algorithm by designing a heuristic based on the considered problem,optimizing the orders of constructing deployment solutions and adding a local search procedure. A series of instances with different sizes are tested and analyzed. The experimental results showthat the designed ACO-DO algorithm performs better than the existing Mixed Integer Linear Programming,ant colony and genetic algorithms.
出处
《电子学报》
EI
CAS
CSCD
北大核心
2016年第1期123-129,共7页
Acta Electronica Sinica
基金
国家自然科学基金(No.61373038
No.61070012)
国家863高技术研究发展计划(No.2012AA011204-01)
关键词
面向服务的软件
部署优化
蚁群算法
性能
service-oriented software
deployment optimization
ant colony algorithm
performance
