Optimization and spatial accessibility for the location of logistic equipment in the specialty coffee production chain in Nariño
DOI:
https://doi.org/10.26507/paper.4175Keywords:
E2SFCA method, Facility location, Logistics optimization, Mixed integer linear programming (MILP), Spatial accessibility, Specialty coffeeAbstract
The Department of Nariño, known for the production of high-quality specialty coffees, faces significant challenges in the marketing and distribution of the product, mainly due to deficiencies in the transport infrastructure and strategic organization of logistics equipment in the territory. This situation affects the competitiveness of the region and the sustainability of production chains. Spatial accessibility, defined as the possibility of accessing opportunities dispersed in space, using the available transport infrastructure, is a determining factor in the competitiveness of agri-food chains, since it directly influences their efficiency and sustainability. This study aims to contribute to strategic decision-making in the specialty coffee production chain by optimizing the location of logistics equipment, such as points of purchase, by maximizing spatial accessibility. The proposed methodology consists of three phases: the first focuses on the characterization of the current network structure or baseline (nodes and arcs). In the second phase, spatial accessibility is assessed by integrating both supply (production zones) and demand (purchase points) using the enhanced two-step floating catchment area (E2SFCA) method, considering three travel time scenarios between origin and destination nodes: 1 hour, 2.5 hours and 4 hours. Finally, in the third phase, optimal locations for logistics facilities are identified by maximizing accessibility, with the implementation of a mixed integer linear programming (MILP) model. This study provides a comprehensive and innovative approach to address the logistics challenges faced by the coffee sector in Nariño, integrating spatial accessibility analysis with optimization models.
Author Biography
Daniel Mauricio Goyes Chaves, Universidad del Valle
Topographic Engineer from the Universidad del Valle, Santiago de Cali, Colombia. PhD student in Engineering with an emphasis in Industrial Engineering at the Universidad del Valle. Member of the group of Transport, Transit and roads GITTV - Logistics and production of the Universidad del Valle. Researcher in the area of Geographic Information Systems (GIS), transport and territory, supply chain management, optimization models.
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