Application of Finite Dynamic Programming to Decision Making in the Use of Industrial Residual Water Treatment Plants
Authors: Oscar Vega Camacho, Andrea Vargas Guevara, Ellery Rowina Ariza
Abstract:
This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its wastewater treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.
Keywords: Decision making, Markov chain, optimization, wastewater.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1096229
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[1] L. Garcés; E. Mejía; J. Santamaría. "La fotocatálisis como alternativa para el tratamiento de aguas residuals” Revista Lasallista de investigación – Vol. 1. N° 1. Pág. 83
[2] E. Idelovitch, y K. Ringskog, "Directions in Development: Wastewater Treatment in Latin America, Old & New Options”, World Bank, Washington, D.C., August 1997.
[3] C. Ramos. "Los residuos en la industria farmacéutica”. Revista CENIC Ciencias Biológicas,2006,Vol.37, No.1
[4] R. Feachem; D. Mara, y M.G. Mc Garry. Water. "Wastes and Health in Hot Climates”. Nueva York: John Wiley and Sons.1977.
[5] R. Palange y A. Zavala. "Water Pollution Control: Guidelines for Project Planning and Financing”. Trabajo Técnico Técnica No.73 del Banco Mundial.1987.
[6] G. Apfel. "Pollution control and abatement in the cosmetic industry”. CTFA Cosmetic Journal 4(1),28-32,1972.
[7] S. Mendonca. "Lagunas de estabilización”. Organización Panamericana de la Salud. Bogotá,Colombia.1999.
[8] M. Rigolala Peña. " Tratamiento de aguas industriales: aguas de proceso y residuals”. México. Alfaomega Grupo Editor, 1999.
[9] U. Ritter. "Environmental pollution aspects at plants for cosmetics production”. 1989. Seifen, Oele, Fette, Wachse115(11/12), 383-386.
[10] C. Ocampo-Martínez. "Model predictive control of waste water systems”. 2010. Springer
[11] F. Berné., J. Cordonnier. "Industrial water treatment”. Institut Francais du petrole publications. 1999
[12] C. A. Sastrya, S. Sundaramoorthy. " Industrial use of freshwater is-a-vis reclaimed municipal wastewater in Madras, India" . 1996. Elsevier Science.
[13] W. Eckenfelder. " Industrial water pollution control" . 2000. McGraw Hill. USA.
[14] G. Fair.; J .Geyer, y D. Okun. "Water and Wastewater Engineering”. 2 Volúmenes. 1966, Nueva York: John Wiley and Sons.
[15] A. Rodríguez. "Tratamientos avanzados de aguas residuales industrials”. Universidad de Alcalá Del Círculo de Innovación en Tecnologías Medioambientales y Energía (CITME), 2006.
[16] C. Jagdish.; R. Arya. Y W. Lardner. "Matemáticas Aplicadas a la Administración y a la Economía”. Pearson Education, México, 2002.
[17] F. Comets, R. Fernandez y P. Ferrari. " Processes with Long Memory: Regenerative Construction and Perfect Simulation”, Ann. Appl. Probab. vol. 123:921-943, 2002.
[18] S. Ross. "Stochastics Processes”. Wiley Series in Probability and Mathematical Statistics: Probability and Mathematical Stat.2002.
[19] P. Ferrari y A. Galvez. " Coupling and Regeneration for stochastic processes”. Notes for a mini course presented in XIII Escuela Venezolana de Matemáticas,2000.
[20] W. Prawda. "Métodos y modelos de investigación de operaciones”. México. Editorial Limusa, 1999.
[21] A. Markov. "Extension of the limit theorems of probability theory to a sum of variables connected in a chain". Reprinted in Appendix B of: R. Howard. Dynamic Probabilistic Systems, volume1: Markov Chains. John Wiley and Sons, 1971.
[22] M. Puterman. "Markov decision processes, discret stochastic dynamic programming”. 2005. Wiley-Interscience Inc.
[23] W. Wayne. "Investigación de operaciones”. 4a Edición. México. International Thomson Editores, 2005.
[24] A. Kistensen. " Dynamic programming and Markov decision processes”. 1996. Textbook notes of herd management.
[25] G. Kalani. "Industrial process control: advances and application”. 2002, Elsevier Science (USA).
[26] F. Sonnenberg., J R. Beck. "Markov models in medical decision making”. Med Decis Making1993;13:322–38.
[27] A. Briggs. M. Sculpher. " An introduction to Markov modelling for economic evaluation”. Pharmacy Economics1998.13:397–409
[28] D. Abler y S.Harris. "Meta-modelling Markov model simulations for cost effectiveness analyses”. Poster presentation at ICTR-PHE, 2012. Radiother Oncol
[29] H. Leff, M. Dada y S. Graves, "An LP planning model for a mental health community support system.” Management Science, 1986, 32, no. 2, 139-155.
[30] Z. Yan, G. Augenbroe y V. Brani. "Uncertainty Analysis in Using Markov Chain Model to Predict Roof Life Cycle Performance”. 2005 International Conference on Durability of Building Materials and Components LYON (France) 17-20.