A Multi-Objective Periodic Vehicle Routing Model for Sustainable Healthcare Waste Collection

Area of Science:

• Operations Research
• Environmental Health
• Logistics Management

Background:

• Infectious waste collection from healthcare facilities (HCF) presents significant operational challenges, balancing safety and cost-effectiveness.
• Current systems often prioritize cost over safety, leading to risks in storage and transportation of infectious materials.
• Tailoring collection frequency to HCF waste generation rates is essential for efficiency and preventing delays.

Purpose of the Study:

• To introduce a novel model, the Sustainable and Load-dependent Periodic Vehicle Routing Problem (S-PVRP), for optimizing infectious waste collection.
• To address the multi-objective challenge of minimizing traveled distance, transportation risk, and storage risk.
• To develop and evaluate solution approaches for the S-PVRP that balance exploration and exploitation.

Main Methods:

• Development of the Sustainable and Load-dependent Periodic Vehicle Routing Problem (S-PVRP) model.
• Design of two multi-objective solution approaches balancing exploration and exploitation.
• Experimental validation using benchmark instances and comparison with state-of-the-art algorithms.

Main Results:

• The proposed S-PVRP model effectively optimizes traveled distance, transportation risk, and storage risk.
• The developed solution approaches demonstrate efficiency in multi-objective optimization.
• The MX-GAOPT algorithm showed competitive performance, outperforming existing algorithms in most tested scenarios.

Conclusions:

• The S-PVRP model provides a robust framework for sustainable and safe infectious waste collection.
• The MX-GAOPT approach offers a superior solution for optimizing HCF waste collection schedules.
• This research contributes to improving operational efficiency and safety in infectious waste management.