Uncertain location–allocation decisions for a bi‐objective two‐stage supply chain network design problem with environmental impacts. Issue 5 (21st April 2020)

• Record Type: Journal Article
• Authors: Mahmoodirad, Ali; Niroomand, Sadegh
• Other Names: Chang Victor guestEditor.; Aljawarneh Shadi A. guestEditor.; Li Chung‐Sheng guestEditor.
• Is Part Of: Expert systems. Volume 37:Issue 5(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-04-21
• Subjects: environmental impact -- fuzzy programming -- multi‐objective optimization -- supply chain network design problem -- uncertainty theory; Expert systems (Computer science); 006.33
• DOI: 10.1111/exsy.12558
• Languages: English
• ISSNs: 0266-4720

Abstract

Abstract: In the cases that the historical data of an uncertain event is not available, belief degree‐based uncertainty theory is a useful tool to reflect such uncertainty. This study focuses on uncertain bi‐objective supply chain network design problem with cost and environmental impacts under uncertainty. As such network may be designed for the first time in a geographical region, this problem is modelled by the concepts of belief degree‐based uncertainty theory. This article is almost the first study on belief degree‐based uncertain supply chain network design problem with environmental impacts. Two approaches such as expected value model and chance‐constrained model are applied to convert the proposed uncertain problem to its crisp form. The obtained crisp forms are solved by some multi‐objective optimization approaches of the literature such as TH, Niroomand, MMNV. A deep computational study with several test problems are performed to study the performance of the crisp models and the solution approaches. According to the results, the obtained crisp formulations are highly sensitive to the changes in the value of the cost parameters. On the other hand, Niroomand and MMNV solution approaches perform better than other solution approaches from the solution quality point of view.