Type-II Fuzzy Multi-Product, Multi-Level, Multi-Period Location–Allocation, Production–Distribution Problem in Supply Chains: Modelling and Optimisation Approach

In this study, the application of type-II fuzzy sets is addressed to design a multi-product, multi-level, multi-period supply chain networks. The proposed model provides integrated approach to make optimal decisions such as location-allocation, production, procurement and distribution subject to ope...

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Bibliographic Details
Published in:Fuzzy information and engineering Vol. 10; no. 2; pp. 260 - 283
Main Authors: J.-Sharahi, Sarah, Khalili-Damghani, Kaveh, Abtahi, Amir-Reza, Rashidi-Komijan, Alireza
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis Group 03.04.2018
Subjects:
Fuzzy sets
Integer programming
Integrated approach
Linear programming
Mathematical models
Optimization
Procurement
Supply chains
ISSN:1616-8658, 1616-8666
Online Access:Get full text
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Summary:In this study, the application of type-II fuzzy sets is addressed to design a multi-product, multi-level, multi-period supply chain networks. The proposed model provides integrated approach to make optimal decisions such as location-allocation, production, procurement and distribution subject to operational and tactical constraints. In the context of fuzzy linear programming, this study involves type-II fuzzy numbers for the right-hand side of constraints regarding three sources of uncertainty: demand, manufacturing and supply. According to fuzzy components considered, a type-II fuzzy mixed-integer linear programming is converted into an equivalent auxiliary crisp model using linear fuzzy type-reducer models. The final models are linear and the global optimum solutions can be achieved using commercial OR softwares. The contributions of this study are three folds: (1) introducing a new integrated supply chain network design problem; (2) considering a solution procedure based on type-II fuzzy sets and (3) presenting a linear fuzzy type-II reducer. Finally, the proposed model and solution approach are illustrated through a numerical example to demonstrate the significance.
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ISSN:1616-8658
1616-8666
DOI:10.1080/16168658.2018.1517978