Outer approximation algorithms to solve semi-infinite environmental pollution problems

Introduction− The traditional approaches of managing the integral estimation of a general function do no solve the prob-lem of fulfilling the constraints in each point of the domain. This is achieved through a semi-infinite formulation of the problem, in which there are great possibilities in modeli...

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Autores:
Fedossova, Alina
Fedosov, Valery
Buitrago Suescún, Oscar Yecid
Tipo de recurso:
Article of journal
Fecha de publicación:
2018
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/2399
Acceso en línea:
https://hdl.handle.net/11323/2399
https://doi.org/10.17981/ingecuc.14.1.2018.02
https://repositorio.cuc.edu.co/
Palabra clave:
Semi-infinite programming
Stochastic programming
Pollution
Outer approximation algorithms
Contamination standards
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dc.title.spa.fl_str_mv Outer approximation algorithms to solve semi-infinite environmental pollution problems
dc.title.translated.spa.fl_str_mv Algoritmos de aproximaciones externas para resolver problemas semi-infinitos de contaminación ambiental
title Outer approximation algorithms to solve semi-infinite environmental pollution problems
spellingShingle Outer approximation algorithms to solve semi-infinite environmental pollution problems
Semi-infinite programming
Stochastic programming
Pollution
Outer approximation algorithms
Contamination standards
title_short Outer approximation algorithms to solve semi-infinite environmental pollution problems
title_full Outer approximation algorithms to solve semi-infinite environmental pollution problems
title_fullStr Outer approximation algorithms to solve semi-infinite environmental pollution problems
title_full_unstemmed Outer approximation algorithms to solve semi-infinite environmental pollution problems
title_sort Outer approximation algorithms to solve semi-infinite environmental pollution problems
dc.creator.fl_str_mv Fedossova, Alina
Fedosov, Valery
Buitrago Suescún, Oscar Yecid
dc.contributor.author.spa.fl_str_mv Fedossova, Alina
Fedosov, Valery
Buitrago Suescún, Oscar Yecid
dc.subject.proposal.eng.fl_str_mv Semi-infinite programming
Stochastic programming
Pollution
Outer approximation algorithms
Contamination standards
topic Semi-infinite programming
Stochastic programming
Pollution
Outer approximation algorithms
Contamination standards
description Introduction− The traditional approaches of managing the integral estimation of a general function do no solve the prob-lem of fulfilling the constraints in each point of the domain. This is achieved through a semi-infinite formulation of the problem, in which there are great possibilities in modeling many practical situations of industrial ecology. Some of them are presented in this paper.Objective−Based on detailed studies ([1]-[3]), the aim of this research paper is to examine the mentioned studies in order to contribute to disseminate SIP (Semi-Infinite Programming) applications in environmental pollution control. Methodology−With regard to the numerical solution a sto-chastic outer approximation algorithm was used, in addition numerical experiments were performed in MATLAB. Results− The obtained results of this work have showed three patterns, the first one enhances the power of emitting pollution sources, taking into account the area landscape, the second one also enhances the power of pollution sources using wind displacement of emissions, finally the third pattern op-erates by improving the pollution of 3D areas between a group of emission sources and purifiers.Conclusions−In conclusion, it can be said that the issue of power from emitting pollution sources, by considering the area landscape and wind displacement of emissions, should be modeled such as a semi-infinite programming trouble. The method used to calculate the algorithm stopping criterion, does not interpret this solution as an additional problem.
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dc.date.accessioned.none.fl_str_mv 2019-02-12T01:32:25Z
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dc.identifier.citation.spa.fl_str_mv A. Fedossova, V. Fedosov y O.Buitrago. “Outer approximation algorithms to solve semi-infinite environment pollution problems” INGE CUC, vol. 14, no. 1, pp. 19-29, 2018 DOI: http://doi.org/10.17981/ingecuc.14.1.2018.02
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identifier_str_mv A. Fedossova, V. Fedosov y O.Buitrago. “Outer approximation algorithms to solve semi-infinite environment pollution problems” INGE CUC, vol. 14, no. 1, pp. 19-29, 2018 DOI: http://doi.org/10.17981/ingecuc.14.1.2018.02
10.17981/ingecuc.14.1.2018.02
2382-4700
Corporación Universidad de la Costa
0122-6517
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/2399
https://doi.org/10.17981/ingecuc.14.1.2018.02
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INGE CUC
dc.relation.references.spa.fl_str_mv V.V. Fedosov and A. Fedossova, “Semi-infinite model limits emissions of enterprises in áreas with a mix landscapes” Jour. of Comp. & Inform. Tecnolog., vol. 86, no. 8, pp. 14-22, 2011.
V.V. Fedosov and A. Fedossova, “Simulation control and limit industrial emissions in the presence of winds displacement”, Jour. of Comp. & Inform. Tecnolog., vol. 87, no. 9, pp. 29-35, 2011.
V.V. Fedosov and A. Fedossova, “Numerical optimization of pollution in 3D área by groups of sources”, Nanoengineering, vol. 7, no. 37, pp. 43-48, 2014.
M. Lopez and G. Still, “Semi-infinite programming,” Eur. J. Oper. Res., vol. 180, pp. 491-518, 2007. https://doi.org/10.1016/j.ejor.2006.08.045
S. K. Zavriev, N.N. Novikova, and A.V., Fedossova, “Stochastic algorithm for solution of convex semi-infinite programming problem with equality and inequality constraints,” Vestnik Mosc. Univer., ser. 15, no. 4, pp. 30-35, 2000.
I. Vaz and E. C. Ferreira, “Air pollution control with sem-iinfinite program,” Appl. Mathem. Model., vol. 33, pp. 1957-1969, 2009. https://doi.org/10.1016/j.apm.2008.05.008
A. Fuduli, M. Gaudioso, G. Giallombardo, and G. Miglionico, “ A partially inexact bundle method for convex semi-infinite minmax problems,” Commun. in Nonlin. Sc.and Numer. Simulation, vol. 21, no. 1, pp. 172-180, 2015. https://doi.org/10.1016/j.cnsns.2014.07.033
A. V. Fedossova, V.V. Kafarov, and D.P. Mahecha Bohórquez, “Solución Numérica del Problema de Control de Contaminación del Aire,” Colom. J. Comp., no. 4, pp. 21- 28, 2003.
Y. V. Volkov and S.K. Zavriev, “A general stochastic outer approximations method,” SIAM J. Control Optim., vol. 35, pp. 1387-1421, 1997. https://doi.org/10.1137/S0363012994263202
A. Gómez Gómez, “Minimización de costos del control de contaminación del aire en un espacio tridimensional”, M.S. thesis, Math. Dept., Univ. Nac. De Colombia, Bogotá, Colombia, 2013.
A Gomez, A Fedossova, R. A. Britto, “A numerical solution for the air pollution control problem in 3D”, DYNA, vol. 84, no. 200, pp. 342-350, 2017. https://doi.org/10.15446/dyna.v84n200.53883
F. Fang, T. Zhang, D. Pavlidis, C.C. Pain, A.G. Buchan, and I.M. Navon, “Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons,” Atmosph. Environ., vol. 96, pp. 96-106, 2014. https://doi.org/10.1016/j.atmosenv.2014.07.021
M. Fallah Shorshani, M. André, C. Bonhomme, and C. Seigneur, “Modelling chain for the effect of road traffic on air and water quality: Techniques, current status and future prospects,” Environ. Modelling & Software, vol. 64, pp. 102-123, 2015. https://doi.org/10.1016/j.envsoft.2014.11.020
V. V. Fedosov, A. Fedossova, “Optimización de emisiones de la red de carreteras de infraestructura urbana”, Ing. Ind., vol.38, no. 2, pp. 143-153, 2017.
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spelling Fedossova, AlinaFedosov, ValeryBuitrago Suescún, Oscar Yecid2019-02-12T01:32:25Z2019-02-12T01:32:25Z2018-01-01A. Fedossova, V. Fedosov y O.Buitrago. “Outer approximation algorithms to solve semi-infinite environment pollution problems” INGE CUC, vol. 14, no. 1, pp. 19-29, 2018 DOI: http://doi.org/10.17981/ingecuc.14.1.2018.02https://hdl.handle.net/11323/2399https://doi.org/10.17981/ingecuc.14.1.2018.0210.17981/ingecuc.14.1.2018.022382-4700Corporación Universidad de la Costa0122-6517REDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/Introduction− The traditional approaches of managing the integral estimation of a general function do no solve the prob-lem of fulfilling the constraints in each point of the domain. This is achieved through a semi-infinite formulation of the problem, in which there are great possibilities in modeling many practical situations of industrial ecology. Some of them are presented in this paper.Objective−Based on detailed studies ([1]-[3]), the aim of this research paper is to examine the mentioned studies in order to contribute to disseminate SIP (Semi-Infinite Programming) applications in environmental pollution control. Methodology−With regard to the numerical solution a sto-chastic outer approximation algorithm was used, in addition numerical experiments were performed in MATLAB. Results− The obtained results of this work have showed three patterns, the first one enhances the power of emitting pollution sources, taking into account the area landscape, the second one also enhances the power of pollution sources using wind displacement of emissions, finally the third pattern op-erates by improving the pollution of 3D areas between a group of emission sources and purifiers.Conclusions−In conclusion, it can be said that the issue of power from emitting pollution sources, by considering the area landscape and wind displacement of emissions, should be modeled such as a semi-infinite programming trouble. The method used to calculate the algorithm stopping criterion, does not interpret this solution as an additional problem.Introducción− Los enfoques tradicionales de gestión de la estimación integral de una función general no resuelven el problema de cumplir con las restricciones en cada punto del dominio. Esto se logra mediante una formulación semi-in-finita del problema, en la que existen grandes posibilidades para modelar muchas situaciones prácticas de la ecología industrial. Algunos de ellos se presentan en este documento.Objetivo− Basándose en estudios detallados ([1]-[3]) el pro-pósito de este artículo es examinarlos y contribuir a difundir las aplicaciones de la programación semi-infinita (SIP) en la solución de problemas de control de contaminación ambiental.Metodología− Para su solución numérica se aplica el algorit-mo estocástico de aproximaciones externas. Los experimentos se realizan en MATLAB. Resultados− Se presentan tres modelos, uno de ellos opti-miza la potencia de emisiones de contaminación por fuentes de contaminación teniendo en cuenta el área de ambiente. Segundo, optimiza la potencia de fuentes de polución con sus desplazamientos causado por el viento y el último optimiza la polución en áreas 3D entre un grupo de contaminantes y un grupo de purificadores.Conclusiones− El problema de optimización de emisiones de las fuentes de contaminación teniendo en cuenta el área y sus desplazamientos por causa del viento puede ser modelado y resuelto como un problema de optimización semi-infinita. El criterio de parada del método utilizado no requiere solución de un problema adicional como normalmente sucede en este tipo de programación.Fedossova, Alina-2dc613a4-c2bd-4765-beab-d2760165162f-0Fedosov, Valery-c2bd0ff0-fb3c-41e1-9a51-e24b7dc2a2ff-0Buitrago Suescún, Oscar Yecid-2cca335e-95c8-41cd-82bd-a64cf2eb567b-011 páginasapplication/pdfengCorporación Universidad de la CostaINGE CUC; Vol. 14, Núm. 1 (2018)INGE CUCINGE CUCV.V. Fedosov and A. Fedossova, “Semi-infinite model limits emissions of enterprises in áreas with a mix landscapes” Jour. of Comp. & Inform. Tecnolog., vol. 86, no. 8, pp. 14-22, 2011.V.V. Fedosov and A. Fedossova, “Simulation control and limit industrial emissions in the presence of winds displacement”, Jour. of Comp. & Inform. Tecnolog., vol. 87, no. 9, pp. 29-35, 2011.V.V. Fedosov and A. Fedossova, “Numerical optimization of pollution in 3D área by groups of sources”, Nanoengineering, vol. 7, no. 37, pp. 43-48, 2014.M. Lopez and G. Still, “Semi-infinite programming,” Eur. J. Oper. Res., vol. 180, pp. 491-518, 2007. https://doi.org/10.1016/j.ejor.2006.08.045S. K. Zavriev, N.N. Novikova, and A.V., Fedossova, “Stochastic algorithm for solution of convex semi-infinite programming problem with equality and inequality constraints,” Vestnik Mosc. Univer., ser. 15, no. 4, pp. 30-35, 2000.I. Vaz and E. C. Ferreira, “Air pollution control with sem-iinfinite program,” Appl. Mathem. Model., vol. 33, pp. 1957-1969, 2009. https://doi.org/10.1016/j.apm.2008.05.008A. Fuduli, M. Gaudioso, G. Giallombardo, and G. Miglionico, “ A partially inexact bundle method for convex semi-infinite minmax problems,” Commun. in Nonlin. Sc.and Numer. Simulation, vol. 21, no. 1, pp. 172-180, 2015. https://doi.org/10.1016/j.cnsns.2014.07.033A. V. Fedossova, V.V. Kafarov, and D.P. Mahecha Bohórquez, “Solución Numérica del Problema de Control de Contaminación del Aire,” Colom. J. Comp., no. 4, pp. 21- 28, 2003.Y. V. Volkov and S.K. Zavriev, “A general stochastic outer approximations method,” SIAM J. Control Optim., vol. 35, pp. 1387-1421, 1997. https://doi.org/10.1137/S0363012994263202A. Gómez Gómez, “Minimización de costos del control de contaminación del aire en un espacio tridimensional”, M.S. thesis, Math. Dept., Univ. Nac. De Colombia, Bogotá, Colombia, 2013.A Gomez, A Fedossova, R. A. Britto, “A numerical solution for the air pollution control problem in 3D”, DYNA, vol. 84, no. 200, pp. 342-350, 2017. https://doi.org/10.15446/dyna.v84n200.53883F. Fang, T. Zhang, D. Pavlidis, C.C. Pain, A.G. Buchan, and I.M. Navon, “Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons,” Atmosph. Environ., vol. 96, pp. 96-106, 2014. https://doi.org/10.1016/j.atmosenv.2014.07.021M. Fallah Shorshani, M. André, C. Bonhomme, and C. Seigneur, “Modelling chain for the effect of road traffic on air and water quality: Techniques, current status and future prospects,” Environ. Modelling & Software, vol. 64, pp. 102-123, 2015. https://doi.org/10.1016/j.envsoft.2014.11.020V. V. Fedosov, A. Fedossova, “Optimización de emisiones de la red de carreteras de infraestructura urbana”, Ing. Ind., vol.38, no. 2, pp. 143-153, 2017.2919114INGE CUCINGE CUChttps://revistascientificas.cuc.edu.co/ingecuc/article/view/1614Outer approximation algorithms to solve semi-infinite environmental pollution problemsAlgoritmos de aproximaciones externas para resolver problemas semi-infinitos de contaminación ambientalArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersioninfo:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Semi-infinite programmingStochastic programmingPollutionOuter approximation algorithmsContamination standardsPublicationORIGINALOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdfOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdfapplication/pdf2424830https://repositorio.cuc.edu.co/bitstreams/beaf6bf7-2214-46c3-b376-b5fb4d2112d4/download174720b1e64ea2b76c8f4290dda7541bMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstreams/f6fbed47-fa96-4c7b-bd4a-b31e3adc46e9/download8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdf.jpgOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdf.jpgimage/jpeg58764https://repositorio.cuc.edu.co/bitstreams/c9733a07-7817-4f3a-bd65-db6bf1608947/download13880e451356c075519d24f7ee643684MD54TEXTOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdf.txtOuter approximation algorithms to solve semi-infinite environmental pollution problems.pdf.txttext/plain45490https://repositorio.cuc.edu.co/bitstreams/7d82e3cb-add5-4c6a-8f00-88b68fe5e5da/downloadec0cbf30429d749b96cf320b0f63f7b9MD5511323/2399oai:repositorio.cuc.edu.co:11323/23992024-09-17 10:15:52.78open.accesshttps://repositorio.cuc.edu.coRepositorio de la Universidad de la Costa CUCrepdigital@cuc.edu.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