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About

I´m a professional and researcher in Logistics and Supply Chain Management, especially interested in Agri-food Supply Networks. I’m currently doing a doctoral program in Engineering and Industrial Management at the Faculty of Engineering of the University of Porto (FEUP). I got my Master´s degree in Industrial Engineering in 2014 at Universidad Distrital Francisco José de Caldas (Bogota-Colombia), where I specialized in Logistics and Operations Research (OR). I´m Industrial Engineer from Fundación Universitaria Agraria de Colombia. I have been working from three fronts which are academia, research and consulting. This allows me to bring organizational practices to academic scenarios as well as to transmit, apply and validate research results in organizations and communities. My experience in the industrial and academic sectors amounts to 14 years. My research interests have a focus on the use of OR & Machine Learning techniques in the framework of Sustainable Supply Chain, especially to find optimal and resilient supply network designs that ensure economic, social and environmental benefits jointly in developing economies.

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Publications

2021

Multi-Objective Optimization to Support the Design of a Sustainable Supply Chain for the Generation of Biofuels from Forest Waste

Authors
Gutierrez Franco, E; Polo, A; Clavijo Buritica, N; Rabelo, L;

Publication
SUSTAINABILITY

Abstract
The production and supply chain management of biofuels from organic waste as raw material has been identified as a promising strategy in the field of renewable energies and circular economy initiatives. This industry involves complex tasks such as strategic land use, feedstock purchasing, production plant location, production capacity strategy, and material flows, which can be solved by mathematical modeling. The study proposed a multi-objective mixed-integer linear programming model to design a sustainable supply chain of biofuels with forest residues from its triple function: economic, environmental, and social. The trade-offs between the proposed objectives were determined with computational results. The proposed objectives were profit maximization, CO2 minimization, and employment generation maximization. Thus, the proposed model serves as a tool for decision-making, allowing the projection of a long-term structure of the biofuel supply chains and contribute to the United Nations Sustainable Development Goals.

2019

Selection of supplier management policies using clustering and fuzzy-AHP in the retail sector

Authors
Buriticá N.C.; Matamoros M.Y.; Castillo F.; Araya E.; Ahumada G.; Gatica G.;

Publication
International Journal of Logistics Systems and Management

Abstract
Supplier development contributes to supply chain integration and performance, thus playing an essential role in any industry. In the retail market, no formal procedures exist for the selection-assignment of supplier development programs, meaning that respective management is complex and unclear given actor and requirement heterogeneities. Multi-criteria techniques are currently used for selection and evaluation processes. However, no models exist that integrate clustering and multi-criteria techniques together to efficiently select-assign supplier development programs. This study proposes a four-phase methodology - diagnosis, program design, assignment, and proposal - that considers supplier clustering through K-means and multi-criteria fuzzification. Additionally, case-study analysis of 149 retail suppliers in Colombia clustered businesses into high (8), medium (32), and low (109) risk sets, each of which was assigned tailored development programs. The obtained results support use of the proposed methodology to improve supply chain performance for organisations with many suppliers requiring development programs.