Methodology of optimization for decision-making in the biodiesel supply network in Colombia.
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Dec 1, 2011
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Abstract
This article proposes a methodology for decision-making based on deterministic and stochastic optimization models to design the network for the supply of palm oil and biodiesel in Colombia. It takes account of the projections of technology available to the transportation sector in scenarios of probabilities associated with the demand for biodiesel in each period of the planning horizon. A base scenario is used to determine the opening of bio-refineries, production plans, optimum flows of raw material and finished products through the network, and the percentage of demand met. This methodology is a flexible took that allows lines of action to be defined depending on the conditions of the supply network, supporting strategic and tactical decision-making.
Keywords
biodiesel, supply network, optimization, analysis of scenarios, planningrede de fornecimento, otimização, análise de cenários, planejamento, biodieselred de suministro, optimización, análisis de escenarios, planeación, biodiesel
References
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Arntzen, B.; Brown, G.; Harrison, T.; and Trafton, L. (1995). Global supply chain management at digital equipment corporation. Interfaces, 25 (1), 69-93.
Biofuels Consulting (2007). Desarrollo y consolidación del mercado de biocombustibles en Colombia. Extraído de http://www.fedebiocombustibles.com/conferencias/presentacion_estudio_bfc_upmea2007.pdf
Birge, J. R. and Louveaux, F. (1997). Introduction to Stochastic Programming. New York: SpringerVerlag, Springer Series in Operations Research.
Carlsson, D. and Rönnqvist, M. (1999). Wood flow problems in the Swedish forestry, The Forestry Research Institute of Sweden Report n. 1.
Carlsson, D.; D'Amours, S.; Martel, A.; and Rönnqvist, M. (2006). Supply chain management in the pulp and paper industry. Working Paper DT-2006-AM-3, Interuniversity Research Center on Enterprise Networks, Logistics and Transportation, CIRRELT. Québec: Université Laval.
Chahin, C.; Cadena, A. y Espinosa, M.A. (2007). Marco normativo y de desarrollo de una metodología de formación de precios de los biocombustibles. Bogotá: Ministerio del Medio Ambiente.
Cohen, M.; and Kleindorfer, P. (1993). Creating value through operations: The legacy of Elwood S. Buffa. In R.K. Sarin (Ed.), Perspectives in Operation Management (Essays in honor of Elwood S. Buffa) (pp. 3-22). Boston: Kluwer Academic Publishers.
Conpes 3510 (2008). Lineamientos de política para promover la producción sostenible de biocombustibles en Colombia. Bogotá: Consejo Nacional de Política Económica y Social, República de Colombia, Departamento Nacional de Planeación.
Epstein, R.; Morales, Serón, J.; and Weintraub, A. (1999). Use of OR systems in the Chilean forest industries. Interfaces, 29 (1) 7-29.
Ezcurra, X. and Plà, L. (2011). AnaPorkDSS: A decision support system to evaluate pig production economics. Proyecto Social, 14, 23-44.
Fedepalma (2005). Actualización de costos de producción de aceite de palma. Bogotá: Fedepalma.
García, R.; Martínez, M.; and Palacios, F. (2007). Tactical and operative optimization of the supply chain in the oil palm industry. Applied Mathematical Modelling.
GAMS (2001). GAMS. The Solver Manuals. Washington, D.C.: gams Development Corporation.
Geoffrion, A.; Graves, G.; and Lee, S. (1978). Strategic distribution system planning: A status report. In A. C. Hax (Ed.), Studies in operations management (pp. 179-204). Amsterdam: North-Holland.
Geoffrion, A.; Graves, G.; and Lee, S. (1982). A management support system for distribution planning. INFO, 20 (4), 287-314.
Geoffrion, A. and Graves, G. (1974). Multicom-modity distribution system design by Benders decomposition. Management Science, 20 (5), 822-844.
Goetschalckx, M.; Vidal, C.; and Dogan, K. (2002). Modeling and design of global logistic system: A review of integrated strategic and tactical models and design algorithms. European Journal of Operational Research, 143 (1), 1-18.
Graham, M. (2011). Food supply. Chain food safety and system management (QA), AgLinkEd Professional Development Conference Harvey 2011, Department of Agriculture and Food, Curtin University (May).
Gunn, E. and Rai, A. (1987). Modelling and decomposition for planning long- term forest harvesting in an integrated industry structure. Canadian Journal of Forest Research 17, 1 507-1518.
Gunnarsson, H. (2007). Optimization approaches to tactical planning problems in the forest industry, Licentiate thesis LiU-TEK-LIC-2003: 70. Swewden: Institute of Technology.
Gunnarsson, H.; Lundgren, J.; and Ro, M. (2001). Optimering kan sa produktionskostnaderna for skogsbr ansle. The Forestry Research Institute of Sweden, Report n. 20 (in Swedish).
Gunnarsson, H.; Lundgren, J.; and Ro, M. (2003), Supply chain modeling of forest fuel. In G.J. Arthaud and T.M. Barrett (Eds.), Systems Analysis in Forest Resources: Proceedings of the Eighth Symposium, September 27-30, 2000, Snowmass Village, Colorado. Norwell: Kluwer Academic Publishers.
Gunnarsson, H.; Ro, M.; and Carlsson, D. (2004), Annual planning of the supply chain and ship routing problem in the pulp industry. In H. Aronsson (Ed.), Nofoma 2004. Book of abstracts. Sweden: Linko Spring.
Gutiérrez, E.; Fuquen, H. y Abril, D. (2010). Planificación integrada de producción y distribución para un conglomerado industrial. Revista Facultad de Ingeniería, 53, 88-105.
Gutiérrez, E.; Cadena, A. y Palacios, F. (2008). Planificación estratégica del sector de biodiesel en Colombia. XIV Congreso Ibero Americano de Investigación de Operaciones, Claio. Cartagena de Indias, Colombia.
Kalenatic, D.; López, C.; González, L. y Rueda, F. (2010). Modelos matemáticos aplicados a logística focalizada. Bogotá: Kalenatic Editor.
Kalenatic, D.; López C. y González, L. (2011) Modelos de Planeación de la Producción en un Contexto de Economías de Escala. Bogotá, Colombia Kalenatic Editor.
López, C.; Kalenatic, D. y Figueroa, J. Secuenciación de Trabajos. Modelos determinísticos. Bogotá, Colombia Kalenatic Editor.
López, E.; Miquel S.; and Plà, L. (2006). Sugar cane transportation in Cuba, a case study. European Journal of Operational Research, 174, 374-386.
Marín, J.; Plà, L.; and Ríos, D. (2005). Inference for some stochastic process models related with sow management. Journal of Applied Statistic, 32 (8), 797-812.
Martell, D.; Gunn, E.; and Weintraub, A. (1998). Forest management challenges for operational researchers. European Journal of Operational Research, 104, 1-17.
Neiro, S. and Pinto, J. (2004). A general modeling framework for the operational planning of petroleum supply chains. Computers and Chemical Engineering, 28, 871-896.
Othman D. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189, 822-840.
Plà, L. (2007). Review of mathematical models for sow herd management. Livestock Production Sciences, 106, 107-119.
Plà, L. (2010). dss in Pig Production Systems. In B. Manos, N. Matsatsinis, K. Paparrizos and J. Papathanasiou (Eds.), Dss in Agriculture, Food and the Environment (101-117). New York: IGI-Global.
Plà, L.; Faulin, F.; and Rodríguez, S. (2009). A linear programming formulation of a semi-Markov model to design pig facilities. Journal of Operational Research Society, 60, 619-625.
Plà, L.; Pomar, C.; and Pomar, J. (2003). A Markov decision sow model representing the productive lifespan of herd sows. Agricultural Systems, 76, 253-272.
Plà, L.; Pomar, C.; and Pomar, J. (2004). A Decision Support System based on a Markov decision sow model. Computers and Electronics in Agriculture, 45 (1-3), 51-69.
Philpott, A. B. and Everett, G. (2001). Supply chain optimisation in the paper industry. Annals of Operations Research, 108, 225-237.
Quariguasi, J. and Bloemhof-Ruwaard, J. (2006). Designing and Evaluating Sustainable Logistics Networks. erim Report Series Research Management.
Rodríguez, S.; Albornoz, V.; and Plà, L. (2009). A two-stage stochastic programming model for scheduling replacement in sow farms. top, 17 (1), 171-189.
Rodríguez, S.; Jensen, T.; Plá, L.; and Kristensen, A. (2011a). Optimal replacement policies and economic value of clinicla observations in sow herds. Livestock Science, 138, 207-219.
Rodríguez, S., Plá, L. and Albornoz, V. (2011b). Modelling tactical planning decisions through a linear optimization model in sow farms. Accepted in Livestock Science.
Shapiro, J. F. (2001). Modeling the Supply Chain. Duxbury, Pacific Grove, CA: Duxbury Thomson Learning Inc.
Shapiro, J. F. (2004). Challenges of strategic supply chain planning and modeling. Computers and Chemical Engineering, 28, 855-861.
Wagner, M. and Meyr, H. (2005). Food and beverages. In H. Stadtler and C. Kilger (Eds.), Supply Chain Management and Advanced Planning (pp. 371-388). Berlin: Springer-Verlag, Berlin.
Weintraub, A.; Epstein, R.; Morales, R.; Serón, J.; and Traverso, P. (1996). A truck scheduling system improves efficiency in the forest industries. Interfaces, 26 (4), 1-12.
Weintraub, A. and Epstein, R. (2002). The supply chain in the forest industry: Models and linkages. In J. Geunes, P. M. Pardalos and H. E. Romeijn (Eds.), Supply chain management: Models, applications, and research directions (pp. 343-362). Dordrecht: Kluwer.
Weintraub, A. and Romero, C. (2006). Operations research models and the management of agricultural and forestry resources: A review and comparison. Interfaces 36 (5), 446-457.
Arntzen, B.; Brown, G.; Harrison, T.; and Trafton, L. (1995). Global supply chain management at digital equipment corporation. Interfaces, 25 (1), 69-93.
Biofuels Consulting (2007). Desarrollo y consolidación del mercado de biocombustibles en Colombia. Extraído de http://www.fedebiocombustibles.com/conferencias/presentacion_estudio_bfc_upmea2007.pdf
Birge, J. R. and Louveaux, F. (1997). Introduction to Stochastic Programming. New York: SpringerVerlag, Springer Series in Operations Research.
Carlsson, D. and Rönnqvist, M. (1999). Wood flow problems in the Swedish forestry, The Forestry Research Institute of Sweden Report n. 1.
Carlsson, D.; D'Amours, S.; Martel, A.; and Rönnqvist, M. (2006). Supply chain management in the pulp and paper industry. Working Paper DT-2006-AM-3, Interuniversity Research Center on Enterprise Networks, Logistics and Transportation, CIRRELT. Québec: Université Laval.
Chahin, C.; Cadena, A. y Espinosa, M.A. (2007). Marco normativo y de desarrollo de una metodología de formación de precios de los biocombustibles. Bogotá: Ministerio del Medio Ambiente.
Cohen, M.; and Kleindorfer, P. (1993). Creating value through operations: The legacy of Elwood S. Buffa. In R.K. Sarin (Ed.), Perspectives in Operation Management (Essays in honor of Elwood S. Buffa) (pp. 3-22). Boston: Kluwer Academic Publishers.
Conpes 3510 (2008). Lineamientos de política para promover la producción sostenible de biocombustibles en Colombia. Bogotá: Consejo Nacional de Política Económica y Social, República de Colombia, Departamento Nacional de Planeación.
Epstein, R.; Morales, Serón, J.; and Weintraub, A. (1999). Use of OR systems in the Chilean forest industries. Interfaces, 29 (1) 7-29.
Ezcurra, X. and Plà, L. (2011). AnaPorkDSS: A decision support system to evaluate pig production economics. Proyecto Social, 14, 23-44.
Fedepalma (2005). Actualización de costos de producción de aceite de palma. Bogotá: Fedepalma.
García, R.; Martínez, M.; and Palacios, F. (2007). Tactical and operative optimization of the supply chain in the oil palm industry. Applied Mathematical Modelling.
GAMS (2001). GAMS. The Solver Manuals. Washington, D.C.: gams Development Corporation.
Geoffrion, A.; Graves, G.; and Lee, S. (1978). Strategic distribution system planning: A status report. In A. C. Hax (Ed.), Studies in operations management (pp. 179-204). Amsterdam: North-Holland.
Geoffrion, A.; Graves, G.; and Lee, S. (1982). A management support system for distribution planning. INFO, 20 (4), 287-314.
Geoffrion, A. and Graves, G. (1974). Multicom-modity distribution system design by Benders decomposition. Management Science, 20 (5), 822-844.
Goetschalckx, M.; Vidal, C.; and Dogan, K. (2002). Modeling and design of global logistic system: A review of integrated strategic and tactical models and design algorithms. European Journal of Operational Research, 143 (1), 1-18.
Graham, M. (2011). Food supply. Chain food safety and system management (QA), AgLinkEd Professional Development Conference Harvey 2011, Department of Agriculture and Food, Curtin University (May).
Gunn, E. and Rai, A. (1987). Modelling and decomposition for planning long- term forest harvesting in an integrated industry structure. Canadian Journal of Forest Research 17, 1 507-1518.
Gunnarsson, H. (2007). Optimization approaches to tactical planning problems in the forest industry, Licentiate thesis LiU-TEK-LIC-2003: 70. Swewden: Institute of Technology.
Gunnarsson, H.; Lundgren, J.; and Ro, M. (2001). Optimering kan sa produktionskostnaderna for skogsbr ansle. The Forestry Research Institute of Sweden, Report n. 20 (in Swedish).
Gunnarsson, H.; Lundgren, J.; and Ro, M. (2003), Supply chain modeling of forest fuel. In G.J. Arthaud and T.M. Barrett (Eds.), Systems Analysis in Forest Resources: Proceedings of the Eighth Symposium, September 27-30, 2000, Snowmass Village, Colorado. Norwell: Kluwer Academic Publishers.
Gunnarsson, H.; Ro, M.; and Carlsson, D. (2004), Annual planning of the supply chain and ship routing problem in the pulp industry. In H. Aronsson (Ed.), Nofoma 2004. Book of abstracts. Sweden: Linko Spring.
Gutiérrez, E.; Fuquen, H. y Abril, D. (2010). Planificación integrada de producción y distribución para un conglomerado industrial. Revista Facultad de Ingeniería, 53, 88-105.
Gutiérrez, E.; Cadena, A. y Palacios, F. (2008). Planificación estratégica del sector de biodiesel en Colombia. XIV Congreso Ibero Americano de Investigación de Operaciones, Claio. Cartagena de Indias, Colombia.
Kalenatic, D.; López, C.; González, L. y Rueda, F. (2010). Modelos matemáticos aplicados a logística focalizada. Bogotá: Kalenatic Editor.
Kalenatic, D.; López C. y González, L. (2011) Modelos de Planeación de la Producción en un Contexto de Economías de Escala. Bogotá, Colombia Kalenatic Editor.
López, C.; Kalenatic, D. y Figueroa, J. Secuenciación de Trabajos. Modelos determinísticos. Bogotá, Colombia Kalenatic Editor.
López, E.; Miquel S.; and Plà, L. (2006). Sugar cane transportation in Cuba, a case study. European Journal of Operational Research, 174, 374-386.
Marín, J.; Plà, L.; and Ríos, D. (2005). Inference for some stochastic process models related with sow management. Journal of Applied Statistic, 32 (8), 797-812.
Martell, D.; Gunn, E.; and Weintraub, A. (1998). Forest management challenges for operational researchers. European Journal of Operational Research, 104, 1-17.
Neiro, S. and Pinto, J. (2004). A general modeling framework for the operational planning of petroleum supply chains. Computers and Chemical Engineering, 28, 871-896.
Othman D. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189, 822-840.
Plà, L. (2007). Review of mathematical models for sow herd management. Livestock Production Sciences, 106, 107-119.
Plà, L. (2010). dss in Pig Production Systems. In B. Manos, N. Matsatsinis, K. Paparrizos and J. Papathanasiou (Eds.), Dss in Agriculture, Food and the Environment (101-117). New York: IGI-Global.
Plà, L.; Faulin, F.; and Rodríguez, S. (2009). A linear programming formulation of a semi-Markov model to design pig facilities. Journal of Operational Research Society, 60, 619-625.
Plà, L.; Pomar, C.; and Pomar, J. (2003). A Markov decision sow model representing the productive lifespan of herd sows. Agricultural Systems, 76, 253-272.
Plà, L.; Pomar, C.; and Pomar, J. (2004). A Decision Support System based on a Markov decision sow model. Computers and Electronics in Agriculture, 45 (1-3), 51-69.
Philpott, A. B. and Everett, G. (2001). Supply chain optimisation in the paper industry. Annals of Operations Research, 108, 225-237.
Quariguasi, J. and Bloemhof-Ruwaard, J. (2006). Designing and Evaluating Sustainable Logistics Networks. erim Report Series Research Management.
Rodríguez, S.; Albornoz, V.; and Plà, L. (2009). A two-stage stochastic programming model for scheduling replacement in sow farms. top, 17 (1), 171-189.
Rodríguez, S.; Jensen, T.; Plá, L.; and Kristensen, A. (2011a). Optimal replacement policies and economic value of clinicla observations in sow herds. Livestock Science, 138, 207-219.
Rodríguez, S., Plá, L. and Albornoz, V. (2011b). Modelling tactical planning decisions through a linear optimization model in sow farms. Accepted in Livestock Science.
Shapiro, J. F. (2001). Modeling the Supply Chain. Duxbury, Pacific Grove, CA: Duxbury Thomson Learning Inc.
Shapiro, J. F. (2004). Challenges of strategic supply chain planning and modeling. Computers and Chemical Engineering, 28, 855-861.
Wagner, M. and Meyr, H. (2005). Food and beverages. In H. Stadtler and C. Kilger (Eds.), Supply Chain Management and Advanced Planning (pp. 371-388). Berlin: Springer-Verlag, Berlin.
Weintraub, A.; Epstein, R.; Morales, R.; Serón, J.; and Traverso, P. (1996). A truck scheduling system improves efficiency in the forest industries. Interfaces, 26 (4), 1-12.
Weintraub, A. and Epstein, R. (2002). The supply chain in the forest industry: Models and linkages. In J. Geunes, P. M. Pardalos and H. E. Romeijn (Eds.), Supply chain management: Models, applications, and research directions (pp. 343-362). Dordrecht: Kluwer.
Weintraub, A. and Romero, C. (2006). Operations research models and the management of agricultural and forestry resources: A review and comparison. Interfaces 36 (5), 446-457.
How to Cite
Gutiérrez Franco, Édgar, Cadena Monroy, Ángela I., Montoya, J., & Palacios, F. (2011). Methodology of optimization for decision-making in the biodiesel supply network in Colombia. Cuadernos De Administración, 24(43). https://doi.org/10.11144/Javeriana.cao24-43.mopt
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