Uncertain supply chain network design considering carbon footprint and social factors using two-stage approach

2017 ◽  
Vol 19 (10) ◽  
pp. 2491-2519 ◽  
Author(s):  
Rakhi Das ◽  
Krishnendu Shaw
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Carbon Footprint ◽  
Social Factors ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Two Stage ◽  
Uncertain Supply

scholarly journals Two-Stage Stochastic Program for Supply Chain Network Design under Facility Disruptions

2021 ◽  
Vol 13 (5) ◽  
pp. 2596
Author(s):  
Kanokporn Kungwalsong ◽  
Chen-Yang Cheng ◽  
Chumpol Yuangyai ◽  
Udom Janjarassuk
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Negative Impact ◽  
Business Environment ◽  
Strategic Decision ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Two Stage ◽  
Supply Chain Disruption

A supply chain disruption is an unanticipated event that disrupts the flow of materials in a supply chain. Any given supply chain disruption could have a significant negative impact on the entire supply chain. Supply chain network designs usually consider two stage of decision process in a business environment. The first stage deals with strategic levels, such as to determine facility locations and their capacity, while the second stage considers in a tactical level, such as production quantity, delivery routing. Each stage’s decision could affect the other stage’s result, and it could not be determined individual. However, supply chain network designs often fail to account for supply chain disruptions. In this paper, this paper proposed a two-stage stochastic programming model for a four-echelon global supply chain network design problem considering possible disruptions at facilities. A modified simulated annealing (SA) algorithm is developed to determine the strategic decision at the first stage. The comparison of traditional supply chain network decision framework shows that under disruption, the stochastic solutions outperform the traditional one. This study demonstrates the managerial viability of the proposed model in designing a supply chain network in which disruptive events are proactively accounted for.

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