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A bi-objective optimization model for the medical supplies' simultaneous pickup and delivery with drones
1School of Management Science and Real Estate, Chongqing University, Chongqing 400000, People's Republic of China.
Computers & Industrial Engineering
|July 6, 2022
Summary
Drones can improve medical supply delivery during emergencies. This study introduces an optimized drone delivery model for faster, safer, and more efficient simultaneous pick-up and delivery, outperforming separate methods.
Area of Science:
- Operations Research
- Logistics Management
- Public Health Preparedness
Background:
- The COVID-19 pandemic highlighted critical needs for rapid, safe medical supply delivery, overcoming traffic limitations and minimizing human contact.
- Existing drone delivery optimization models are insufficient for the demands of public health emergencies, particularly concerning simultaneous pick-up and delivery.
- Efficient logistics are crucial for timely medical supply distribution in crisis situations.
Purpose of the Study:
- To propose a novel bi-objective mixed integer programming model for the multi-trip drone location routing problem.
- To enable simultaneous pick-up and delivery of medical supplies, optimizing delivery time and location accuracy.
- To address the limitations of current models in emergency medical logistics.
Main Methods:
- Development of a bi-objective mixed integer programming model for drone-based simultaneous pick-up and delivery.
- Design and implementation of a modified Non-dominated Sorting Genetic Algorithm II (NSGA-II) with double-layer coding to solve the proposed model.
- Conducting multiple data experiments to validate the algorithm's performance and compare delivery modes.
Main Results:
- The proposed optimization model with simultaneous pick-up and delivery significantly reduces delivery time compared to separate pick-up and delivery modes.
- The simultaneous mode demonstrates enhanced safety by enabling contactless delivery, crucial for infectious disease pandemics.
- The modified NSGA-II algorithm effectively solves the complex routing problem, showing superior performance in experimental data.
Conclusions:
- Simultaneous pick-up and delivery via drones offers a more efficient, safer, and resource-saving solution for medical supply logistics in emergencies.
- The developed optimization model and modified NSGA-II algorithm provide a robust framework for managing drone-based emergency medical deliveries.
- Sensitivity analysis offers valuable insights for refining drone delivery management strategies in public health crises.
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