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Research on optimal decision-making of cloud manufacturing service provider based on grey correlation analysis and TOPSIS

机译:基于灰色相关分析和Topsis的云制造服务提供商最优决策研究

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摘要

It is of great practical significance to optimise the decision-making of cloud manufacturing service providers, which can ensure the efficient operation of the cloud manufacturing services. In order to effectively optimise, this paper constructs the evaluation index system, sorts out 7 important evaluation indexes. A method is proposed on the basis of the TOPSIS method and Grey Correlation Analysis (GRA), which is a decision-making method combining static distance and dynamic trend, and make the evaluation results more reasonable. In addition, in order to reflect the true weight of the high dimensional index, the evaluation model of projection pursuit index is established. The improved Particle Swarm Optimisation (PSO) algorithm is used to optimise the projection index function and model parameters, and to obtain the objective weights of evaluation indexes. Then the objective weights combine with the subjective weights obtained by the Analytic hierarchy process (AHP), which makes the weights of the evaluation indexes achieve the unity of subjective and objective. Finally, 20 sets of simulation examples are given to illustrate the feasibility and effectiveness of the proposed method.
机译:优化云制造服务提供商的决策是具有很大的实际意义,可以确保云制造服务的有效运行。为了有效优化,本文构建了评估指标体系,分类了7个重要评估指标。基于TOPSIS方法和灰色相关分析(GRA)来提出一种方法,这是一种结合静态距离和动态趋势的决策方法,并使评估结果更合理。此外,为了反映高维指数的真正重量,建立了投影追踪指标的评估模型。改进的粒子群优化(PSO)算法用于优化投影索引功能和模型参数,并获得评估指标的客观权重。然后,客观权重与分析层次处理(AHP)获得的主观权重组合,这使得评估指标的权重实现主观和目标的统一。最后,给出了20组模拟实施例来说明所提出的方法的可行性和有效性。

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