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Data-driven smart freight fleet management amid epidemic disruptions: A framework and case study
Carlos D Paternina-Arboleda1, Diana G Ramirez-Rios2, Karenina N Zaballa3
1San Diego State University, San Diego, CA, 92182, USA. cpaternina@sdsu.edu.
Health Care Management Science
|July 17, 2026
Summary
This study presents a data-driven framework for intelligent freight fleet management, enhancing operational efficiency and driver safety during epidemic disruptions. The system optimizes route planning, driver allocation, and health protocols for resilient logistics.
Area of Science:
- Operations Research
- Logistics Management
- Data Science
Background:
- Freight fleets face significant operational challenges during epidemic disruptions.
- Existing management strategies often lack adaptability to health crises.
- Data analytics and smart technologies offer potential solutions for resilient fleet operations.
Purpose of the Study:
- To introduce a comprehensive data-driven framework for intelligent freight fleet management.
- To address challenges in route planning, driver allocation, and health risk management during epidemics.
- To demonstrate the framework's efficacy using a simulated case study with real geospatial data.
Main Methods:
- Development of a data-driven framework integrating data analytics and decision-making methodologies.
- Implementation of intelligent algorithms for route planning and driver allocation.
- Inclusion of health risk management protocols within the operational framework.
- Validation through a simulated case study utilizing real geospatial data.
Main Results:
- Significant enhancements in overall operational efficiency.
- Marked reduction in operational risks associated with disruptions.
- Notable elevation in driver safety protocols and well-being.
- Demonstrated real-world applicability and efficacy of the proposed framework.
Conclusions:
- The data-driven framework provides a robust solution for intelligent freight fleet management during epidemic disruptions.
- The study highlights the importance of integrating data analytics and smart technologies for enhanced resilience.
- Organizations can leverage this framework to improve adaptability, safety, and efficiency in logistics operations.
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