Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14365/1441
Title: A novel multi-objective optimization approach for sustainable supply chain: A case study in packaging industry
Authors: Resat, H. Giray
Unsal, Berkcan
Keywords: Sustainable supply chain
Multi-objective optimization
Mixed-integer linear programming
Analytic hierarchy process
Epsilon-Constraint Method
Decision-Making
Selection
Network
Design
Publisher: Elsevier
Abstract: This study presents a novel two-stage hybrid solution method designed for sustainable supply chain systems and applied in packaging industry. The proposed solution algorithm includes two main stages; Analytic Hierarchy Process (AHP) method that is applied to select the most efficient suppliers by considering different performance indicators of company and a mixed-integer linear multi-objective mathematical model that is proposed to optimize the design of the sustainable supply chain in terms of total cost, time and social factors. Mathematical modelling approach and data analysis are presented to help decision makers. Minimization of cost, time; and maximization of sustainability by using augmented epsilon-constraint method are outlined by using proposed model. Pareto solution sets of the multi-objective mathematical programming problem are obtained by using GAMS language and environment. Sensitivity analyses are made to highlight the details of illustrative cases based on real-life data from packaging industry. (C) 2019 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
URI: https://doi.org/10.1016/j.spc.2019.04.008
https://hdl.handle.net/20.500.14365/1441
ISSN: 2352-5509
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File SizeFormat 
488.pdf
  Restricted Access
2.08 MBAdobe PDFView/Open    Request a copy
Show full item record



CORE Recommender

SCOPUSTM   
Citations

47
checked on Sep 4, 2024

WEB OF SCIENCETM
Citations

39
checked on Sep 4, 2024

Page view(s)

40
checked on Sep 9, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.