REVISTA POLITÉCNICA, Vol. 16, Núm. 31

10.33571/rpolitec Revista Politécnica Revista Politécnica 1900-2351 2256-5353 Politécnico Colombiano Jaime Isaza Cadavid 10.33571/rpolitec.v16n31a9 Artículo Modelación matemática en estudio de agro-cadenas: una revisión de literatura Muñoz Pinzón Dairo Steven 1 Polo Roa Andrés 1 Sierra Mantilla Elvira Julieth 1 Rueda Uribe Diego 1 dairo.munoz@outlook.com 6 2020 16 31 110 137 2 12 2019 28 5 2020

El sector agrícola es el eje fundamental que mueve la economía del mundo, permite la generación de productos agrícolas y pecuarios para el abastecimiento de pequeñas y grandes ciudades. En los países subdesarrollados es necesaria la participación de la industria y la academia para el fortalecimiento de los sistemas productivos, esto a partir de la inyección de tecnología, así como la transferencia y apropiación de conocimiento en el sector. Un enfoque usado para el fortalecimiento del sector, es el estudio de las cadenas de suministro agrícolas (agro-cadenas) a partir de la modelación matemática, la cual permite el tratamiento de datos y facilita la toma de decisiones de orden estratégico, táctico y/o operativo. En el presente trabajo se realizó una revisión de literatura sobre la aplicación de la modelación matemática en el estudio de las Agro-cadenas durante los últimos 20 años. Se concluye del estudio que, existe un interés bastante grande por la comunidad académico-científica por fortalecer el sector agrícola en diferentes países como Estados Unidos, Brasil, india y Holanda entre otros. En el 36% de los trabajos consultados se emplean modelos de simulación estocástica, permitiendo abordar problemas complejos que involucran incertidumbre en con comportamiento de los datos. Además, en el 70% de los trabajos consultados, se utilizan modelos heurísticos para resolver problemas de diseño y distribución en agrocadenas, y el 30% restante requiere el uso de meta-heurísticas porque requieren resolver problemas con múltiples respuestas dada la complejidad de los datos. La modelación matemática se ha convertido en una herramienta de gran utilidad para la solución de problemas latentes en la agro-cadenas, facilita el tratamiento de datos y la toma de decisiones complejas, principalmente durante el diseño de cadena, el abastecimiento de producto y control de costos, tiempos de entrega e impactos ambientales, entre otras variables importantes.

Cadena de suministro Modelos matemáticos Revisión de literatura Agrocadenas

no

AGRADECIMIENTOS

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The agricultural sector is the fundamental axis that moves the world economy, it allows the generation of agricultural and livestock products to supply small and large cities. In underdeveloped countries, the participation of industry and academia is necessary to strengthen production systems, this based on the injection of technology, as well as the transfer and appropriation of knowledge in the sector. An approach used to strengthen the sector is the study of agricultural supply chains (agro-chains) based on mathematical modeling, that allows data processing and facilitates strategic, tactical or operational decision-making. We conducted a review of the literature on the application of mathematical models in the study of agricultural chains during the last 20 years. The study concludes that there is a fairly great interest by the academic-scientific community to strengthen the agricultural sector in different countries such as the United States, Brazil, India and the Netherlands, among others. Stochastic simulation models are used in 36% of the consulted works, allowing complex problems involving uncertainty in data behavior to be addressed. Also, in 70% of the works consulted, heuristic models are used to solve design and distribution problems in agro-chains, and the remaining 30% require the use of metaheuristics because they require solving problems with multiple responses given the complexity of the data. Mathematical modeling has become a very useful tool for solving latent problems in agro-chains, it facilitates data processing and complex decision-making, mainly during chain design, product supply and control of costs, delivery times and environmental impacts, among other important variables.

Supply chain Mathematical models Literature review Agricultural chains

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Revista Politécnica 
ISSN: 1900-2351
ISSN: 2256-5353 (En línea)

DOI:  10.33571/rpolitec

Editada por: Politécnico Colombiano Jaime Isaza Cadavid