A novel method for MCDM and evaluation of manufacturing services using collaborative filtering and IVIF theory

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Abstract

The new era of global cooperation and competition has created challenges for manufacturing enterprises in selecting optimal services and collaboration enterprises. Multi-criteria decision making (MCDM) and evaluation has been applied in the domain of manufacturing service to address these issues. This study proposes a novel method for MCDM and evaluation of manufacturing services using collaborative filtering and interval-valued intuitionistic fuzzy (IVIF) theory. Quality of service (QoS)-aware collaborative filtering predicts missing QoS values in an IVIF rating matrix that is normalized from initial matrices that employ mixed numerical terms. An interval-valued intuitionistic fuzzy weighted arithmetic (IIFWA) aggregation operator derived from IVIF theory is utilized to evaluate and select the optimal service(s) or supplier(s). An illustrative example of manufacturing service evaluation and comparison are provided to validate the effectiveness and practicability of the proposed method.

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Zhang, W., Zhang, S., Zhang, S., & Yu, D. (2016). A novel method for MCDM and evaluation of manufacturing services using collaborative filtering and IVIF theory. Journal of Algorithms and Computational Technology, 10(1), 40–51. https://doi.org/10.1177/1748301815618304

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