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A multi-period multi-season multi-objective mathematical model for guaranteeing the viability of supply chains under fluctuations: a healthcare closed-loop supply chain application

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Abstract

Fluctuations in supply chains’ input, such as demand, purchasing, transportation, and production costs, could negatively affect the supply chain’s efficiency and responsiveness. Several fluctuations lead to several types of shorter time intervals per period, resulting in high complexity in supply chain planning. This paper defines each time interval with the stable value of a parameter as a Season and considers different numbers of seasons from different lengths for each parameter per period. It proposes a multi-period multi-season multi-objective mixed-integer mathematical model to formulate several viability strategies under fluctuations in a closed-loop supply chain (CLSC) planning. In addition, a framework of viable healthcare supplier selection is proposed, involving several criteria, such as sustainability, resiliency, and Industry 4.0 adaptation, and using the fuzzy analytical hierarchy process. The proposed model is solved in a healthcare case study of face mask production using the optimality grade method and CPLEX solver. The results showed the need for forty-eight seasonal suppliers’ layoffs, seven production lines’ seasonal layoffs, several seasonal capacity regulations, and different levels of seasonal storage to reach a viable CLSC. In addition, the seasonal price and production cost forecasting should be as accurate as possible due to their significant share in the total costs. Also, sensitivity analysis showed the considerable role of seasonal demand variation on the layoff strategy of viability.

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  1. Department of Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran

    Zahra Hussaini, Arash Nemati & Mohammad Mahdi Paydar

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  1. Zahra Hussaini
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Hussaini, Z., Nemati, A. & Paydar, M.M. A multi-period multi-season multi-objective mathematical model for guaranteeing the viability of supply chains under fluctuations: a healthcare closed-loop supply chain application. Ann Oper Res (2023). https://doi.org/10.1007/s10479-023-05783-8

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