A sustainable and resilient supply chain (RS-SCM) by using synchronisation and load-sharing approach: application in the oil and gas refinery

Abstract

Nowadays sustainable and resilient supply chain management (R&S-SCM) is an interesting and in the meantime vital problem that has grabbed the attention of many researchers. This study is an effort to investigate the simultaneous design of sustainable and resilient flow in the supply chain. To achieve a sustainable and resilient supply chain, there is a wide variety of strategies depending on their impacts on different industries and the features of their supply chain. The fuzzy QFD method is designed to select the most appropriate strategy in the study. Two approaches are used for this purpose. Early planning in sustainable mode is formulated assuming that all members of the network are healthy and final planning in the reactive approach to destruction which formulates the return to the original state in the shortest possible time, cost and scenario-based status. A hybrid priority-based Genetic Algorithm (pb-GA) and simulated annealing algorithm (SA) is developed in two phases to find the optimal solutions. Response Surface Methodology (RSM) method is used to adjust significant parameters for the algorithm. Several test problems are generated showing that the proposed metaheuristic algorithm can find good solutions in reasonable time spans.

KEYWORDS:

• Sustainable and resilient supply chain management
• quality function deployment
• priority-based encoding method
• simulated annealing

Acknowledgements

The authors would like to ILAM Gas Treating Company for its steady support through the period of the study and for providing substantial input during the different phases of the project.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Mohsen Khezeli

Mohsen Khezeli is a PhD student in the Faculty of Industrial Engineering Department at the Science and Research Branch of Islamic Azad University.

Esmaeil Najafi

Esmail Najafi is the Associate Professor in the Faculty of Industrial Engineering Department at the Science and Research Branch of Islamic Azad University.

Mohammad Haji Molana

Mohammad Haji Molana is the Associate Professor in the Faculty of Industrial Engineering Department at the Science and Research Branch of Islamic Azad University.

Masoud Seidi

Masoud Seidi is the Associate Professor of the Faculty of Engineering Department of Ilam University.