Automotive Parts Purchasing Using the Fuzzy MOMIP Model of Reliability Objective with Uncertain Weights

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) mo...

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Bibliographic Details
Published in:Studies in Informatics and Control Vol. 30; no. 2; pp. 5 - 20
Main Authors: XU, Zeshui, CHEN, Jia jia, YE, Jianmei, ZHANG, Jianchuan
Format: Journal Article
Language:English
Published: Bucharest National Institute for Research and Development in Informatics 25.06.2021
Subjects:
Algorithms
Automobile industry
Automotive parts
Decision making
Integer programming
Optimization
Product reliability
Production capacity
Purchasing
Reputations
Sensors
Suppliers
Supply chain management
Sustainability
ISSN:1220-1766, 1841-429X
Online Access:Get full text
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Summary: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.
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ISSN:1220-1766
1841-429X
DOI:10.24846/v30i2y202101