A capacity planning approach for sustainable-resilient supply chain network design under uncertainty: A case study of vaccine supply chain. (September 2021)

• Record Type: Journal Article
• Authors: Sazvar, Zeinab; Tafakkori, Keivan; Oladzad, Nastaran; Nayeri, Sina
• Is Part Of: Computers & industrial engineering. Volume 159(2021)
• Publication Date: 2021-09
• Subjects: Supply chain network design -- Sustainability -- Resiliency -- Robust fuzzy optimization -- Multi-choice goal programming with utility function; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2021.107406
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Designing a sustainable- resilient supply chain network under uncertainty. Sustainability and resiliency interactions on supply chain decisions are discussed. A real case study of influenza vaccine supply chain is investigated . Sensitivity analysis and the managerial suggestions are provided. Abstract: This paper introduces a multi-objective mathematical model to design a sustainable-resilient supply chain based on strategic and tactical decision levels. The resolution is to proactively plan for an optimal configuration to satisfy customer demands when the firm is highly vulnerable to operational and disruption risks. Compared to previous studies, we take the application of capacity planning in terms of redundancy to design a supply chain network that is resilient toward the demand-side by an optimization framework. A real-world influenza vaccine supply chain is studied to validate the proposed model and examine the tradeoff between resilience and sustainability. A robust fuzzy optimization approach is employed to cope with uncertainties. Then, the multi-objective model is solved by applying multi-choice goal programming with a utility function approach. Accordingly, managerial insights are suggested by analyzing the effects of structural parameters on the quantitative results. It is revealed that having redundancies in the supply chain does not always increase the total costs.