文章基本信息

标题：Automotive Parts Purchasing Using the Fuzzy MOMIP Model of Reliability Objective with Uncertain Weights
本地全文：下载
作者：Zeshui XU ; Jia jia CHEN ; Jianmei YE 等
期刊名称：Studies in Informatics and Control Journal
印刷版ISSN：1220-1766
出版年度：2021
卷号：30
期号：2
页码：5-20
DOI：10.24846/v30i2y202101
出版社：National Institute for R&D in Informatics
摘要：This paper develops an effective order allocation method considering a reliability objective, fuzzy information provided by candidate suppliers and uncertain objective weights, and uses it to provide automotive parts procurement solutions. A fuzzy multi-objective mixed integer programming (MOMIP) model with uncertain objective weights is formulated to minimize total cost, the unqualified automotive parts and to maximize supply reliability, obtained by a synthetical evaluation of five criteria including financial status stability, technique of product reliability, quality reliability, service and environment sustainability. An extended interactive algorithm is developed to solve the model. By applying it in a case of sensor parts purchasing under an operational context of industry 4.0, the result shows that the reliability objective is effective in supplier selection and order allocations; and that the interactive algorithm only requiring the preference order on the objective weights from decision makers is also effective.
其他关键词：Fuzzy MOMIP model, Reliability objective, Uncertain objective weights, Extended interactive algorithm, Industry 4.0.