Designing a new sustainable Test Kit supply chain network utilizing Internet of Things

Area of Science:

• Operations Research
• Supply Chain Management
• Public Health

Background:

• The COVID-19 pandemic created significant economic strain, particularly for low-income nations, highlighting challenges in procuring and distributing essential test kits.
• Developing countries faced technological and financial hurdles in accessing and deploying COVID-19 testing capabilities.
• Existing supply chains struggled to meet the demand for rapid and secure distribution of diagnostic tools.

Purpose of the Study:

• To propose the first sustainable COVID-19 test kit supply chain network (STKSCN) addressing distribution, logistics, and waste management.
• To develop an Internet of Things (IoT)-based platform to improve the speed, accuracy, and security of the test kit supply chain.
• To present and evaluate advanced mathematical models and meta-heuristic algorithms for optimizing the STKSCN.

Main Methods:

• A multi-objective, multi-period, multi-resource mathematical model was extended for the STKSCN.
• An Internet of Things (IoT) platform was designed for online patient registration and appointment scheduling.
• Mathematical optimization techniques including AUGMECON2, NSGA-II, and PESA-II were employed, with the Taguchi method for parameter tuning.

Main Results:

• The PESA-II algorithm demonstrated superior efficiency and performance compared to NSGA-II and AUGMECON2 based on defined metrics and computational time.
• The proposed IoT platform enhances the network's speed, accuracy, and security.
• A case study in Iran validated the effectiveness of the developed STKSCN model.

Conclusions:

• The developed sustainable COVID-19 test kit supply chain network (STKSCN) effectively addresses distribution and management challenges.
• The integration of IoT technology and advanced meta-heuristic algorithms like PESA-II offers a robust solution for optimizing healthcare supply chains.
• The study provides a scalable and efficient model for managing essential medical supplies during global health crises.