Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model

Area of Science:

• Operations Research
• Environmental Science
• Public Health

Background:

• Municipal solid waste (MSW) management is vital for public health and environmental protection.
• Medical waste, particularly from infectious diseases like COVID-19, poses significant environmental and health risks if not managed properly.
• Effective medical waste management strategies are essential to mitigate these risks.

Purpose of the Study:

• To develop a bi-objective mixed-integer linear programming model for optimizing medical waste management during the COVID-19 outbreak.
• To simultaneously minimize total management costs and population exposure risks to pollution.
• To incorporate novel, realistic assumptions into the waste management model.

Main Methods:

• A bi-objective mixed-integer linear programming model was formulated.
• The model integrates location-routing, time-windowed green vehicle routing, vehicle scheduling, vehicle failure, split delivery, population risk, and load-dependent fuel consumption.
• A fuzzy goal programming approach was employed to solve the bi-objective model.

Main Results:

• The study successfully developed and applied a comprehensive model for medical waste management.
• The model demonstrated the capability to balance cost reduction with pollution risk minimization.
• The fuzzy goal programming approach proved efficient for solving the complex bi-objective optimization problem.

Conclusions:

• The proposed model offers an effective framework for managing medical waste, especially during health crises like the COVID-19 pandemic.
• Integrating realistic logistical and risk factors leads to more robust and sustainable waste management solutions.
• The methodology provides a valuable tool for policymakers and waste management authorities to enhance operational efficiency and public safety.