A robust reverse pharmaceutical supply chain design considering perishability and sustainable development objectives

Fatemeh Shekoohi Tolgari () and Naeme Zarrinpoor ()
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Fatemeh Shekoohi Tolgari: Shiraz University of Technology
Naeme Zarrinpoor: Shiraz University of Technology

Annals of Operations Research, 2024, vol. 340, issue 2, No 11, 1033 pages

Abstract: Abstract The pharmaceutical supply chain (PSC) is a highly important strategic issue in the healthcare domain because of its significant effect on human wellbeing and healthcare costs. This paper provides a mathematical optimization model to design a PSC by considering the drug's corruption. Given the importance of the sustainable development goals, three objectives are considered: economic, social, and environmental. The cost of fixed installation, transportation, holding, collection, distribution, recycling and disposal is reduced by the economic objective. A reduction in greenhouse gas emissions, water use, and nonrenewable energy consumption is achieved by the environmental objective. Based on the social objective, the number of employment opportunities, economic growth, job satisfaction, and national self-sufficiency are all increased, while the number of days lost due to work-related accidents decreases. To achieve the weight of elements in environmental and social objectives, the fuzzy best–worst method is used. Due to the inherent uncertainty in the PSC, its main parameters are referred to as unpredictable, which calls for a robust optimization approach to eliminate the model parameters’ uncertainty. A fuzzy programming approach is used to solve the developed model. Numerical evidence drawn from a practical case shows that the suggested model is efficacious and valid. We suggest that the priorities and challenges of sustainable growth contribute to the determination of the PSC’s managerial and operational characteristics.

Keywords: Perishable pharmaceutical supply chain; Sustainable development goals; Uncertainty; Robust optimization; Fuzzy best–worst method (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s10479-024-05871-3

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