Paper Info
Title
Novel robust fuzzy programming for closed-loop supply chain network design under hybrid uncertainty.
Abstract
In this paper, a mixed-integer nonlinear programming model is developed for a general edible oil closed loop supply chain network design problem under hybrid uncertainty which is then transformed to its linear counterpart. In order to cope with the hybrid uncertainty in input parameters, scenario-based and fuzzy- based parameters, a new approach is proposed including a novel robust fuzzy programming and an efficient method based on the Me measure. Furthermore, the performance of the proposed model is compared with that of other models. Finally, numerical studies and simulation are performed to verify our mathematical formulation and demonstrate the benefits of the proposed model.
Year
DOI
Venue
2019
10.3233/JIFS-18117
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
Keywords
Field
DocType
Mixed-integer programming,edible oil supply chain,closed loop supply chain,Network design,robust possibilistic programming,stochastic programming
Mathematical optimization,Supply chain network,Fuzzy programming,Artificial intelligence,Mathematics,Machine learning
Journal
Volume
Issue
ISSN
37
5.0
1064-1246
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Ehsan Dehghan100.34
Maghsoud Amiri2819.31
Mohsen Shafiei Nikabadi374.58
armin jabbarzadeh4415.69