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中文摘要：
为了更好地解决服务质量感知的云服务优化组合问题,首先对社会认知算法进行了改进,提出了面向离散型优化问题的模仿学习方法以及基于多次变异的观察学习方法。然后使用改进的社会认知算法对服务质量感知的云服务优化组合问题进行了求解。实验结果表明,改进的社会认知算法具有较强的搜索能力和较快的收敛速度,并且具有较强的推广性,可以用来求解其他离散型优化问题。
英文摘要：
In order to address the problem of QoS-aware cloud services optimal composition,this paper firstly improved the social cognitive optimization,and proposed a kind of imitation learning method for discrete optimization problems and designed a kind of observation learning method.Then,it used the improved SCO algorithm to solve the QoS-aware cloud service optimal composition problem.The experiment results show that improved social cognitive optimal algorithm has strong search ability and fast convergence rate,it also can be used to solve other discrete optimization problems.
同期刊论文项目
同项目期刊论文
Social learning optimization (SLO) algorithm paradigm and its application in QoS-aware cloud service
Developing Objective Sensitivity Analysis of Periodic Systems: Case Studies of Biological Oscillator
Computational Experiment Approach to Controlled Evolution of Procurement Pattern in Cluster Supply C
Framework of Analyzing Service-Centric Cluster Supply Chain: A Case Study of Collaborative Procureme
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