Edgar Gutiérrez-Franco is a scholar and practitioner working at the intersection of operations research, artificial intelligence and supply chain management. He is an associate lecturer in operations research at the University of Central Florida (UCF). Previously, he directed the Center for Applied Analytics and Technology at Universidad Externado de Colombia, where he led applied research initiatives and graduate programs in digital transformation, business analytics and information technology. He is also president of the Latin America and Caribbean Chapter of the Production and Operations Management Society (POMS LA&C), and in 2025 he led the winning team of the INFORMS CODE Program, a competitive international award recognizing impactful research on operational challenges in emerging economies.

His research applies advanced analytics, optimization, simulation and artificial intelligence to improve decision-making in complex operational environments, and he has published more than 20 peer-reviewed journal articles and books with Taylor & Francis, Emerald Publishing and Nova Science Publishers. He has maintained an active affiliation with MIT’s Center for Transportation and Logistics as visiting scholar, postdoctoral associate, research affiliate and guest lecturer, and has led multidisciplinary industry teams delivering optimization, simulation and AI-driven decision support systems across beverage, agribusiness, manufacturing, construction and retail supply chains.

• Gutierrez-Franco, E., Mejia-Argueta, C., & Rabelo, L. (2021). Data-driven methodology to support long-lasting logistics and decision-making for urban last-mile operations. Sustainability, 13(11), 6230.


• Fiok, K., Karwowski, W., Gutierrez, E., & Wilamowski, M. (2021). Analysis of sentiment in tweets addressed to a single domain-specific Twitter account: Comparison of model performance and explainability of predictions. Expert Systems with Applications, 186, 115771.


• Gutierrez-Franco, E., Medina, P., & Mejia, C. (2025, June). Enhancing Multi-echelon Home Improvement Supply Chain Responsiveness Through Machine Learning-Enabled Inventory Segmentation and Positioning. In North American Conference on Industrial Engineering and Operations Management-Computer Science Tracks (pp. 283-300). Springer.


• Gutierrez-Franco, E., Polo, A., Clavijo-Buritica, N., & Rabelo, L. (2021). Multi-Objective Optimization to Support the Design of a Sustainable Supply Chain for the Generation of Biofuels from Forest Waste. Sustainability, 13(14), 7774.


• Gutiérrez, E., Montoya J., Mancera H., Cabra J., "Modeling the Supply Chain in the Semi-Integrated Steel Industry: A Case Study in Colombia" Logistik Management Systeme. ISBN: 978-3-7908-2361-5 ed: Springer Verlag Berlin Heidelberg, 2009.


• Montoya J., Gutiérrez E., Blanco, E., "Conceptual framework for measuring carbon footprint in supply chains." Production Planning and Control, Vol. 4, No. 26, 2014.


• Montoya J, Gutierrez, E., Pirachican, C., "Project scheduling with limited resources using a genetic algorithm," International Journal of Project Management, ISSN: 0263-7863, Vol. 28 fasc.6, p. 619 - 628. 2010.


• Betts, K., Gutierrez-Franco, E., & Ponce-Cueto, E. (2022). Key metrics to measure the performance and impact of reusable packaging in circular supply chains. Frontiers in Sustainability, 3, 910215