Redesign of the sustainable wheat-flour-bread supply chain network under uncertainty: An improved robust optimization

Abolghasem Yousefi-Babadi, Ali Bozorgi-Amiri, Reza Tavakkoli-Moghaddam*, Kannan Govindan

*Kontaktforfatter

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

Abstract

With the passage of time, the grains supply chain may go out of optimality and be disrupted, so it is necessary to redesign the supply chain to avoid incurring irreparable costs. Because of the occurring grain supply chain sub-optimization event as time passes, this paper redesigns a wheat-flour-bread supply chain network considering sustainable development under uncertainty. For this reason, both facility and transaction networks are investigated, and newly redesigned networks are presented. First, a new definition of sustainable development pillars in supply chains is proposed, and then a four-objective mixed-integer linear programming model is presented. Due to uncertainties in the economic, environmental, social, and technical parameters of the presented model, a robust optimization method is developed to deal with them. Then, an augmented weighted Tchebycheff method, followed by the Lagrangian relaxation algorithm, is applied for solving the four-objective model. Next, a real-case study is performed to appraise the efficiency of the model. Finally, a sensitivity analysis is conducted on the critical parameters of the model to analyze the behavior of different objective functions. With the model's solution, the redesign of the supply chain provides an enhancement in the economic, environmental, social, infrastructural, and final objective functions by about 18, 23, 31, 37, and 20%, respectively.

OriginalsprogEngelsk
Artikelnummer103215
TidsskriftTransportation Research Part E: Logistics and Transportation Review
Vol/bind176
Antal sider37
ISSN1366-5545
DOI
StatusUdgivet - aug. 2023

Bibliografisk note

Funding Information:
This research was partially supported by a Grant from the Danida Fellowship Centre (Project no. 20- M11SDU).

Publisher Copyright:
© 2023 Elsevier Ltd

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