S-ABC——面向服务领域的人工蜂群算法范型

发布时间：2018-04-27 09:59

本文选题：服务领域特性 + 人工蜂群算法　；参考：《计算机学报》2015年11期

【摘要】：服务计算优化问题(如服务选择、服务组合、服务资源调度等)随着云计算、物联网、大数据的快速发展而变得日益复杂.另一方面,各服务行业在其长期演化中逐渐形成了特有的领域特性(如服务先验性、关联性、相似性等).这些特性对服务优化问题求解有重要影响,如果对其考虑不充分,将导致服务优化问题求解的效率与效果不理想.因此,如何构建面向服务领域的服务优化算法范型及高效求解算法与优化策略成为亟待解决的关键问题.文中分析了服务领域特性对服务优化问题求解的影响规律,据此改进了人工蜂群算法的优化策略,提出了面向服务领域的人工蜂群算法范型(Service domain-oriented Artificial Bee Colony algorithm paradigm,S-ABC),阐述了S-ABC范型的优化机理,并通过验证实验证实了该算法范型的优化效果.该研究工作为利用服务领域特性指导服务优化问题求解算法的设计提供了新的研究思路和方法,深化了群体智能算法在服务领域的应用,扩展了群体智能算法的优化理论.
[Abstract]:With the rapid development of cloud computing, Internet of things and big data, service computing optimization problems (such as service selection, service composition, service resource scheduling, etc.) have become increasingly complex. On the other hand, various service industries have gradually formed special domain characteristics (such as service priori, relevance, similarity, etc.) in their long-term evolution. These characteristics have an important impact on the service optimization problem solving, if it is not fully considered, it will lead to the service optimization problem solving efficiency and effect is not ideal. Therefore, how to construct service-oriented service optimization algorithm paradigm and efficient algorithm and optimization strategy becomes a key problem to be solved. In this paper, the influence of service domain characteristics on the solution of service optimization problem is analyzed, based on which the optimization strategy of artificial bee colony algorithm is improved. In this paper, a service oriented artificial bee colony algorithm is presented, which is called Service domain-oriented Artificial Bee Colony algorithm paradigm S-ABC, and the optimization mechanism of S-ABC norm is expounded, and the optimization effect of this algorithm is verified. This work provides a new research idea and method for the design of service optimization problem solving algorithm using service domain characteristics, deepens the application of swarm intelligence algorithm in service field, and extends the optimization theory of swarm intelligence algorithm.
【作者单位】：哈尔滨工业大学计算机科学与技术学院;
【基金】：国家自然科学基金(61033005,61472106,61272187,61300124)资助~~
【分类号】：TP393.09;TP18

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