Publicado

2017-04-01

Gestión de pedidos de medicamentos oncológicos usando programación estocástica

Orden management for oncology drugs using stochastic programming

Palabras clave:

Administración de cadena de suministros, gestión de inventarios, programación estocástica de dos etapas (es)
Supply chain management, inventory management, two-stage stochastic programming (en)

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Este artículo presenta un modelo de programación estocástica que busca resolver los problemas de incertidumbre asociados a la gestión de inventarios y que se encuentran presentes en la cadena de suministros de medicamentos oncológicos. Como técnica de solución se usa la programación estocástica de dos etapas propuesta por Dantzig (Dantzig, 1955) y que es de fácil implementación a través del software General Algebraic Modeling System (GAMS). La aplicación del modelo se lleva a cabo considerando tres medicamentos de alta rotación y costo como son: Sandostatina, Exjade y Tasigna, usados para los tratamientos tales como leucemia, tumores endocrinos e insuficiencia renal.
This paper presents a stochastic programming model that seeks to solve the problems of uncertainty associated with inventory management present in the supply chain develops cancer drugs. As a solution technique the two-stage stochastic programming given by Dantzig (Dantzig, 1955) is used. The resulting model is solved with the "General Algebraic Modeling System" (GAMS) software. The application of the model is carried out considering three drugs high turnover and cost as: Sandostatin, Exjade and Tasigna, which are used for treatments such as leukemia, endocrine tumors and renal failure.

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Dantzig, G.B., Linear programming under uncertainty, Manage. Sci., 1(3-4), pp. 197-206, 1955.

Uthayakumar, R. and Priyan, S., Pharmaceutical supply chain and inventory management strategies: Optimization for a pharmaceutical company and a hospital, Oper. Res. Heal. Care, 2(3), pp. 52-64, 2013. DOI: 10.1016/j.orhc.2013.08.001

Castrellón-Torres, W., Torres-Acosta, J.P. and Adarme-Jaimes, J.H., Model for the logistics distribution of medicines in the Colombian public health program, DYNA, 81(187), pp. 257-266, 2014. DOI: 10.15446/dyna.v81n186.46107

Masoumi, H., Yu, M. and Nagurney, A., A supply chain generalized network oligopoly model for pharmaceuticals under brand differentiation and perishability, Transp. Res. Part E Logist. Transp. Rev., 48(4), pp. 762-780, 2012. DOI: 10.1016/j.tre.2012.01.001

Arango, M.D. and Serna, C.A., A memetic algorithm for the traveling salesman problem, IEEE Lat. Am. Trans., 13(8), pp. 2674-2679, 2015. DOI: 10.1109/TLA.2015.7332148

Arango-Serna, M.D., Adarme-Jaimes, W. y Zapata-Cortés, J.A., Inventarios colaborativos en la optimización de la cadena de suministros, DYNA, 80(181), pp. 71-80, 2013.

Shah, N., Pharmaceutical supply chains: Key issues and strategies for optimisation, Comput. Chem. Eng., 28(6–7), pp. 929-941, 2004. DOI: 10.1016/j.compchemeng.2003.09.022

King, A.J. and Wallace, S.W., Modeling with stochastic programming. New York: Springer, 2010. DOI: 10.1007/978-0-387-87817-1

Tarim, S.A., Manandhar, S. and Walsh, T., Stochastic constraint programming: A scenario-based approach, Constraints, 11(1), pp. 53-80, 2006. DOI: 10.1007/s10601-006-6849-7

Chen, Z.-L., Li, S. and Tirupati, D., A scenario-based stochastic programming approach for technology and capacity planning, Comput. Oper. Res., 29(7), pp. 781-806, 2002. DOI: 10.1016/S0305-0548(00)00076-9

Arango-Serna, M.D., Serna, C.A. y Perez, G., Aplicaciones de lógica difusa a las cadenas de suministro, Rev. Av. en Sist. e Informática, 5(3), pp. 117-126, 2008.

Adarme-Jaimes, W., Arango-Serna, M.D. y Cogollo-Flórez, J.M., Medición del desempeño para cadenas de abastecimiento en ambientes de imprecisión usando lógica difusa, Ing. y Univ., 16(1), pp. 95-115, 2012. DOI: 10.1144/1288

Choi, J., Realff, M.J. and Lee, J.H., Stochastic dynamic programming with localized cost-to-go approximators: Application to large scale supply chain management under demand uncertainty, Chem. Eng. Res. Des., 83(6), pp. 752-758, 2005. DOI: 10.1205/cherd.04375

Parpas, P. and Rustem, B., Global optimization of the scenario generation and portfolio selection problems, in Computational Science and its applications - ICCSA 2006, 1, in: Gavrilovan, M., Gervasi, O., Kumar, V. and Taniar, D., Eds. Berlin: Springer, 2006, pp. 908-917. DOI: 10.1007/11751595

Hammami, R., Temponi, C. and Frein, Y., A scenario-based stochastic model for supplier selection in global context with multiple buyers, currency fluctuation uncertainties, and price discounts, Eur. J. Oper. Res., 233(1), pp. 159-170, 2014. DOI: 10.1016/j.ejor.2013.08.020

Huang, K. and Küçükyavuz, S., On stochastic lot-sizing problems with random lead times, Oper. Res. Lett., 36(3), pp. 303-308, 2008. DOI: 10.1016/j.orl.2007.10.009

Karuppiah, R., Martín, M. and Grossmann, I.E., A simple heuristic for reducing the number of scenarios in two-stage stochastic programming, Comput. Chem. Eng., 34(8), pp. 1246-1255, 2010. DOI: 10.1016/j.compchemeng.2009.10.009

Marufuzzaman, M., Eksioglu, S.D. and Huang, Y., Two-stage stochastic programming supply chain model for biodiesel production via wastewater treatment, Comput. Oper. Res., 49, pp. 1-17, 2014. DOI: 10.1016/j.cor.2014.03.010

Sodhi, M.S. and Tang, C.S., Modeling supply-chain planning under demand uncertainty using stochastic programming: A survey motivated by asset-liability management, Int. J. Prod. Econ., 121(2), pp. 728-738, 2009. DOI: 10.1016/j.ijpe.2009.02.009

Santoso, T., Ahmed,S., Goetschalckx, M. and Shapiro, A., A stochastic programming approach for supply chain network design under uncertainty, Eur. J. Oper. Res., 167(1), pp. 96-115, 2005. DOI: 10.1016/j.ejor.2004.01.046

Osmani, A. and Zhang, J., Stochastic optimization of a multi-feedstock lignocellulosic-based bioethanol supply chain under multiple uncertainties, Energy, 59, pp. 157-172, 2013. DOI: 10.1016/j.energy.2013.07.043

Guerrero, W.J., Yeung, T.G. and Guéret, C., Joint-optimization of inventory policies on a multi-product multi-echelon pharmaceutical system with batching and ordering constraints, Eur. J. Oper. Res., 231(1), pp. 98-108, 2013. DOI: 10.1016/j.ejor.2013.05.030

Sousa, R.T., Liu, S., Papageorgiou, L.G. and Shah, N., Global supply chain planning for pharmaceuticals, Chem. Eng. Res. Des., 89(11), pp. 2396-2409, 2011. DOI: 10.1016/j.cherd.2011.04.005

Izadi, A. and Kimiagari, A.N., Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: A case study in pharmaceutical industry, J. Ind. Eng. Int., 10(50), pp. 1-9, 2014. DOI: 10.1007/s40092-014-0050-1

Escudero, L.F. and Kamesam, P.V., On solving stochastic production planning problems via scenario modelling, Top, 3(1), pp. 69-95, 1995. DOI: 10.1007/BF02574804

Schumann, Implementatio of the scenario generation scheme. Deliverable D4.4, Eur. Comm. DGIII Ind., 1999.