Full-Arranged EDAS Model for Cloud Manufacturing Service Optimization
How to select services that satisfy users from among many candidate cloud manufacturing services is the key to the efficient development of cloud man-ufacturing.Aiming at the uncertainty of cloud manufacturing service optimization evaluation information,the risk aversion psychology of cloud manufacturing deman-ders,and the system multiplier effect of their overall evaluation system,a hesitant fuzzy full array EDAS model is proposed to achieve accurate optimization.Under the framework of EDAS,this model represents completely divergent opinions through hesitant fuzzy sets,introduces positive and negative ideal solutions that reflect ex-treme situations into the EDAS model for solution,constructs an indicator quality evaluation measure that can characterize risk aversion psychology,and utilizes a full array of indicators to aggregate to reflect the multiplier effect of the indicator system.Finally,it is applied to solve the cloud manufacturing service optimization problem of Yunnan Yunnei Power Group to verify the appropriateness and superiority of the proposed method.
Cloud manufacturing servicesEDAStotal arrangement polymeriza-tionhesitant fuzzy set
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