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A Multiuser Manufacturing Resource Service Composition Method Based on the Bees Algorithm

机译:基于Bees算法的多用户制造资源服务组合方法

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摘要

In order to realize an optimal resource service allocation in current open and service-oriented manufacturing model, multiuser resource service composition (RSC) is modeled as a combinational and constrained multiobjective problem. The model takes into account both subjective and objective quality of service (QoS) properties as representatives to evaluate a solution. The QoS properties aggregation and evaluation techniques are based on existing researches. The basic Bees Algorithm is tailored for finding a near optimal solution to the model, since the basic version is only proposed to find a desired solution in continuous domain and thus not suitable for solving the problem modeled in our study. Particular rules are designed for handling the constraints and finding Pareto optimality. In addition, the established model introduces a trusted service set to each user so that the algorithm could start by searching in the neighbor of more reliable service chains (known as seeds) than those randomly generated. The advantages of these techniques are validated by experiments in terms of success rate, searching speed, ability of avoiding ingenuity, and so forth. The results demonstrate the effectiveness of the proposed method in handling multiuser RSC problems.
机译:为了在当前的开放式和面向服务的制造模型中实现最佳的资源服务分配,将多用户资源服务组合(RSC)建模为一个组合且受约束的多目标问题。该模型同时考虑了主观和客观服务质量(QoS)属性,作为评估解决方案的代表。 QoS属性聚合和评估技术基于现有研究。基本的Bees算法是为查找模型的最佳解决方案而量身定制的,因为仅提出了基本版本才能在连续域中找到所需的解决方案,因此不适合解决我们研究中建模的问题。设计特定规则来处理约束并找到帕累托最优性。此外,已建立的模型向每个用户介绍了一个受信任的服务集,因此该算法可以通过在比随机生成的服务链更可靠的邻居(称为种子)中进行搜索来开始。这些技术的优势已通过实验在成功率,搜索速度,避免独创性的能力等方面得到了验证。结果证明了该方法在处理多用户RSC问题中的有效性。

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