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Modelo de localización y ruteo para el transporte del gas asociado a la producción de crudo en campos petroleros

dc.contributor.advisorTorres Ramos, Andres Felipe
dc.contributor.advisorReyes Rubiano, Lorena Silvana
dc.contributor.authorGutiérrez Güiza, Jorge Alexander
dc.date.accessioned2018-05-31T14:35:13Z
dc.date.available2018-05-31T14:35:13Z
dc.date.issued2018
dc.identifier.citationAgencia Nacional de Hidrocarburos. (2017). Estadísticas de Producción. Recuperado Julio 7, 2017, de http://www.anh.gov.co/Operaciones-Regalias-y-Participaciones/Sistema-Integrado-deOperaciones/Paginas/Estadisticas-de-Produccion.aspx
dc.identifier.citationAgencia Nacional de Hidrocarburos - Colombia. (2016). Shape de pozos 2015 Agencia Nacional de Hidrocarburos - Colombia. Recuperado de http://www.anh.gov.co/Paginas/inicio/defaultANH.aspx
dc.identifier.citationAhmadi, A., & Seddighi, A. H. (2013). A location-routing problem with disruption risk. Transportation Research Part E: Logistics and Transportation Review, 53(1), 63–82
dc.identifier.citationAl-Mudhafar, W. J., Al-Jawad, M. S., & Al-Shamma, D. A. (2010). Using optimization techniques for determining optimal locations of additional oil wells in South Rumaila oil field. Society of Petroleum Engineers - International Oil and Gas Conference and Exhibition in China 2010, IOGCEC, 1(SPE 130054), 159–178
dc.identifier.citationAlexander, B., & Sergey, S. (2014). A Metaheuristic Approach for the Problem of Motor Fuel Distribution. Procedia Computer Science, 31(Itqm), 143–150.
dc.identifier.citationAliabadi, A., & Shamekhi, A. (2012). Recent Developments in Gas Flaring and Venting Reduction. In SPE 152024.
dc.identifier.citationAlumur, S., & Kara, B. Y. (2007). A new model for the hazardous waste location-routing problem. Computers and Operations Research, 34(5), 1406–1423
dc.identifier.citationAmbrosino, D., Sciomachen, A., & Scutellà, M. G. (2009). A heuristic based on multi-exchange techniques for a regional fleet assignment location-routing problem. Computers and Operations Research, 36(2), 442–460.
dc.identifier.citationAnghinolfi, D., Paolucci, M., & Tonelli, F. (2016). A Vehicle Routing Problem with Time Windows Approach for Planning Service Operations in Gas Distribution Network of a Metropolitan Area. IFAC-PapersOnLine, 49(12), 1365–1370.
dc.identifier.citationBarrero, D., Pardo, A., Vargas, C. a., & Martínez, J. F. (2007). Colombian Sedimentary Basins: Nomenclature, boundaries and Petroleum Geology, a New Proposal. Agencia Nacional de Hidrocarburos - A.N.H.-. Agencia Nacional de Hidrocarburos. https://doi.org/ISBN: 978-958- 98237-0-5
dc.identifier.citationBarreto, S., Ferreira, C., Paixão, J., & Santos, B. S. (2007). Using clustering analysis in a capacitated location-routing problem. European Journal of Operational Research, 179(3), 968–977. https://doi.org/10.1016/j.ejor.2005.06.074
dc.identifier.citationBiobaku, T., Lim, G., Cho, J., Parsaei, H., & Kim, S. (2015). Liquefied Natural Gas Ship Route Planning: A Risk Analysis Approach. Procedia Manufacturing, 3, 1319–1326.
dc.identifier.citationBlanquero, R., Carrizosa, E., Boglárka, G., & Nogales-gómez, A. (2016). p -facility Huff location problem on networks. European Journal of Operational Research, 255(1), 34–42.
dc.identifier.citationBozorgi-Amiri, A., & Khorsi, M. (2016). A dynamic multi-objective location-routing model for relief logistic planning under uncertainty on demand, travel time, and cost parameters. International Journal of Advanced Manufacturing Technology, 85(5–8), 1633–1648.
dc.identifier.citationCaballero, R., González, M., Guerrero, F. M., Molina, J., & Paralera, C. (2007). Solving a multiobjective location routing problem with a metaheuristic based on tabu search. Application to a real case in Andalusia. European Journal of Operational Research, 177(3), 1751–1763.
dc.identifier.citationChbichib, A., Mellouli, R., & Chabchoub, H. (2012). Profitable Vehicle Routing Problem with Multiple Trips: Modeling and Variable Neighborhood Descent Algorithm. American Journal of Operational Research, 2(6), 104–119.
dc.identifier.citationCoelho, V. N., Grasas, A., Ramalhinho, H., Coelho, I. M., Souza, M. J. F., & Cruz, R. C. (2016). An ILS-based algorithm to solve a large-scale real heterogeneous fleet VRP with multi-trips and docking constraints. European Journal of Operational Research, 250(2), 367–376.
dc.identifier.citationCoutinho-Rodrigues, J., Tralhão, L., & Alçada-Almeida, L. (2012). Solving a location-routing problem with a multiobjective approach: The design of urban evacuation plans. Journal of Transport Geography, 22, 206–218.
dc.identifier.citationde Camargo, R. S., de Miranda, G., & Løkketangen, A. (2013). A new formulation and an exact approach for the many-to-many hub location-routing problem. Applied Mathematical Modelling, 37(12–13), 7465–7480.
dc.identifier.citationDrexl, M., & Schneider, M. (2015). A survey of variants and extensions of the location-routing problem. European Journal of Operational Research, 241(2), 283–308.
dc.identifier.citationElvidge, C. D., Baugh, K. E., Tuttle, B. T., Howard, A. T., Pack, D. W., Milesi, C., & Erwin, E. H. (2007). A twelve year record of national and global gas flaring volumes estimated using satellite data. Recuperado de http://siteresources.worldbank.org/INTGGFR/Resources/DMSP_flares_20070530_b-sm.pdf
dc.identifier.citationEmam, E. A. (2015). Gas Flaring in Industry: an Overview. Petroleum & Coal, 57(5), 532–555.
dc.identifier.citationEnergy Information Administration. (2017). U.S. No 2 Diesel Retail Prices. Recuperado Julio 26, 2017, de https://www.eia.gov/dnav/pet/hist/LeafHandler.ashx?n=PET&s=EMD_EPD2D_PTE_NUS_D PG&f=W
dc.identifier.citationEscobar, J. W., Linfati, R., Baldoquin, M. G., & Toth, P. (2014). A Granular Variable Tabu Neighborhood Search for the capacitated location-routing problem. Transportation Research Part B: Methodological, 67, 344–356.
dc.identifier.citationFazel Zarandi, M. H., Hemmati, A., Davari, S., & Burhan Turksen, I. (2013). Capacitated locationrouting problem with time windows under uncertainty. Knowledge-Based Systems, 37, 480– 489.
dc.identifier.citationFernandez Cuesta, E., Andersson, H., Fagerholt, K., & Laporte, G. (2017). Vessel routing with pickups and deliveries: An application to the supply of offshore oil platforms. Computers and Operations Research, 79(March 2016), 140–147.
dc.identifier.citationFiorot, H., Alvarenga, R. De, & Rosa, A. L. da S. (2016). Planning The Diesel Supply For Offshore Platforms By A Mathematical Model Based On The Vehicle Routing Problem With Replenishment. Transportation Research Procedia, 18(June), 11–18.
dc.identifier.citationGao, J., He, C., & You, F. (2017). Shale Gas Process and Supply Chain Optimization. In Advances in Energy Systems Engineering (Vol. 1, pp. 21–46).
dc.identifier.citationGao, S., Wang, Y., Cheng, J., Inazumi, Y., & Tang, Z. (2016). Ant colony optimization with clustering for solving the dynamic location routing problem. Applied Mathematics and Computation, 285, 149–173.
dc.identifier.citationGuerrero, W. J., Prodhon, C., Velasco, N., & Amaya, C. A. (2013). Hybrid heuristic for the inventory location-routing problem with deterministic demand. International Journal of Production Economics, 146(1), 359–370.
dc.identifier.citationHanczar, P. (2012). A Fuel Distribution Problem – Application of New Multi-item Inventory Routing Formulation. Procedia - Social and Behavioral Sciences, 54, 726–735.
dc.identifier.citationHashemi Doulabi, S. H., & Seifi, A. (2013). Lower and upper bounds for location-arc routing problems with vehicle capacity constraints. European Journal of Operational Research, 224(1), 189–208.
dc.identifier.citationHe, Z., Khatu, G., Tenenbaum, E., Li, W., & Han, Z. (2016). Flared Gas Monetization with Modular Gas-to-Liquid Units : Oilfield Conversion of Associated Gas into Petrol at SmallScales. In Abu Dhabi International Petroleum Exhibition & Conference SPE-183510-MS.
dc.identifier.citationHernandez, F., Feillet, D., Giroudeau, R., & Naud, O. (2016). Branch-and-price algorithms for the solution of the multi-trip vehicle routing problem with time windows. European Journal of Operational Research, 249(2), 551–559.
dc.identifier.citationKaraoglan, I., & Altiparmak, F. (2015). A memetic algorithm for the capacitated location-routing problem with mixed backhauls. Computers and Operations Research, 55, 200–216.
dc.identifier.citationKaraoglan, I., Altiparmak, F., Kara, I., & Dengiz, B. (2011). A branch and cut algorithm for the location-routing problem with simultaneous pickup and delivery. European Journal of Operational Research, 211(2), 318–332.
dc.identifier.citationKaraoglan, I., Altiparmak, F., Kara, I., & Dengiz, B. (2012). The location-routing problem with simultaneous pickup and delivery: Formulations and a heuristic approach. Omega, 40(4), 465– 477.
dc.identifier.citationKoc, Ç. (2016). A unified-adaptive large neighborhood search metaheuristic for periodic locationrouting problems. Transportation Research Part C: Emerging Technologies, 68, 265–284.
dc.identifier.citationKovacs, A. A., Parragh, S. N., & Hartl, R. F. (2015). The multi-objective generalized consistent vehicle routing problem. European Journal of Operational Research, 247(2), 441–458.
dc.identifier.citationLi, J., Chu, F., & Prins, C. (2009). Lower and upper bounds for a capacitated plant location problem with multicommodity flow. Computers & Operations Research, 36, 3019-- 3030.
dc.identifier.citationLi, Y., Hu, G., & Wright, M. M. (2015). An optimization model for sequential fast pyrolysis facility location-allocation under renewable fuel standard. Energy, 93, 1165–1172.
dc.identifier.citationLinfati, R., Escobar, J. W., & Gatica, G. (2014). A Metaheuristic Algorithm for the Location Routing Problem with Heterogeneous Fleet. Ingeniería y Ciencia, 10(19), 55–76.
dc.identifier.citationLopes, R. B., Ferreira, C., Santos, B. S., & Barreto, S. (2013). A taxonomical analysis, current methods and objectives on location-routing problems. International Transactions in Operational Research, 20(6), 795–822.
dc.identifier.citationLopes, R. B., Plastria, F., Ferreira, C., & Santos, B. S. (2014). Location-arc routing problem: Heuristic approaches and test instances. Computers and Operations Research, 43, 309–317.
dc.identifier.citationLópez, E., Akhavani, R., Dieulle, L., Labadie, N., & Medaglia, A. L. (2016). On the combined maintenance and routing optimization problem. Reliability Engineering and System Safety, 145, 199–214.
dc.identifier.citationMarín, A., Nickel, S., Puerto, J., & Velten, S. (2009). A flexible model and efficient solution strategies for discrete location problems. Discrete Applied Mathematics, 157(157), 1128– 1145.
dc.identifier.citationMarkov, I., Varone, S., & Bierlaire, M. (2016). Integrating a heterogeneous fixed fleet and a flexible assignment of destination depots in the waste collection VRP with intermediate facilities. Transportation Research Part B: Methodological, 84, 256–273.
dc.identifier.citationMartínez, I. A., Molina, J., Ángel, F., Gómez, T., & Caballero, R. (2014). Solving a bi-objective Transportation Location Routing Problem by metaheuristic algorithms. European Journal of Operational Research, 234, 25–36.
dc.identifier.citationMotherwell, J., & Weinbel, C. (2014). Facility siting and routing with a focus on sustainability. In SPE International Conference on Health, Safety and Environment 2014: The Journey Continues SPE 168534 Facility. Recuperado de http://www.scopus.com/inward/record.url?eid=2-s2.0- 84905860521&partnerID=40&md5=247a7320ef56ac02265bc4cb3261d9b7
dc.identifier.citationMousavi, S. M., & Tavakkoli-Moghaddam, R. (2013). A hybrid simulated annealing algorithm for location and routing scheduling problems with cross-docking in the supply chain. Journal of Manufacturing Systems, 32(2), 335–347.
dc.identifier.citationOcampo, E. M. T., Castaño, A. H. D., & Zuluaga, A. H. E. (2016). Desempeño de las técnicas de agrupamiento para resolver el problema de ruteo con múltiples depósitos. Tecno Lógicas, 19(36), 49–62.
dc.identifier.citationPérez, C. E. T., & Flores, J. L. M. (n.d.). Revisión y programación de modelos de optimización como una plataforma en GAMS-CPLEX para problemas de ruteo de vehículos .
dc.identifier.citationPFC Energy. (2007). Using Russia’s Associated Gas: Prepared for the Global Gas Flaring Reduction Partnership and the World Bank.
dc.identifier.citationProdhon, C. (2011). A hybrid evolutionary algorithm for the periodic location-routing problem. European Journal of Operational Research, 210(2), 204–212.
dc.identifier.citationProdhon, C., & Prins, C. (2014). A survey of recent research on location-routing problems. European Journal of Operational Research, 238(1), 1–17.
dc.identifier.citationQian, J., & Eglese, R. (2016). Fuel emissions optimization in vehicle routing problems with timevarying speeds. European Journal of Operational Research, 248(3), 840–848.
dc.identifier.citationRajović, V., Kiss, F., Maravić, N., & Bera, O. (2016). Environmental flows and life cycle assessment of associated petroleum gas utilization via combined heat and power plants and heat boilers at oil fields. Energy Conversion and Management, 118, 96–104
dc.identifier.citationRakke, J. G., Stålhane, M., Moe, C. R., Christiansen, M., Andersson, H., Fagerholt, K., & Norstad, I. (2011). A rolling horizon heuristic for creating a liquefied natural gas annual delivery program. Transportation Research Part C: Emerging Technologies, 19(5), 896–911.
dc.identifier.citationRamírez, E. Á., Torres, J. R. M., & Muñoz, A. F. (2016). MODELO DE RUTEO PARA LA RECOLECCIÓN DE MUESTRA DE FLUIDO DE POZO EN CAMPO QUIFA – META COLOMBIA.
dc.identifier.citationRazali, N. M. (2015). An Efficient Genetic Algorithm for Large Scale Vehicle Routing Problem Subject to Precedence Constraints. Procedia - Social and Behavioral Sciences, 195, 1922– 1931.
dc.identifier.citationRieck, J., Ehrenberg, C., & Zimmermann, J. (2014). Many-to-many location-routing with inter-hub transport and multi-commodity pickup-and-delivery. European Journal of Operational Research, 236(3), 863–878.
dc.identifier.citationRiquelme, J. P., Gamache, M., & Langevin, A. (2016). Location arc routing problem with inventory constraints. Computers and Operations Research, 76, 84–94.
dc.identifier.citationRocha, R., Grossmann, I. E., & Poggi de Aragão, M. V. S. (2009). Petroleum allocation at PETROBRAS: Mathematical model and a solution algorithm. Computers and Chemical Engineering, 33(12), 2123–2133.
dc.identifier.citationRodina, A. (2016). Burning through : reducing associated petroleum gas flaring to enhance natural. Law In Transition Journal, 83–91.
dc.identifier.citationRodríguez-Martín, I., Salazar-González, J. J., & Yaman, H. (2014). A branch-and-cut algorithm for the hub location and routing problem. Computers and Operations Research, 50, 161–174.
dc.identifier.citationRosa, R. de A., Machado, A. M., Ribeiro, G. M., & Mauri, G. R. (2016). A mathematical model and a Clustering Search metaheuristic for planning the helicopter transportation of employees to the production platforms of oil and gas. Computers and Industrial Engineering, 101, 303–312.
dc.identifier.citationSalhi, S., Imran, A., & Wassan, N. A. (2014). The multi-depot vehicle routing problem with heterogeneous vehicle fl eet : Formulation and a variable neighborhood search implementation. Computers and Operation Research, 52, 315–325.
dc.identifier.citationSamanlioglu, F. (2013). A multi-objective mathematical model for the industrial hazardous waste location-routing problem. European Journal of Operational Research, 226(2), 332–340.
dc.identifier.citationShishebori, D., Dayarian, I., Jabbarzadeh, A., & Barzinpour, F. (2014). A new hybrid approach to discrete multiple facility location problem. The International Journal of Advanced Manufacturing Technology, 71(1–4), 127–139.
dc.identifier.citationSiddiqui, A. W., & Verma, M. (2015). A bi-objective approach to routing and scheduling maritime transportation of crude oil. Transportation Research Part D: Transport and Environment, 37, 65–78.
dc.identifier.citationTan, S. H., & Barton, P. I. (2015). Optimal dynamic allocation of mobile plants to monetize associated or stranded natural gas, part I: Bakken shale play case study. Energy, 93, 1581– 1594
dc.identifier.citationThe World Bank. (2015). Regional Gas Seminar. Maputo. Recuperado de http://docplayer.net/42912426-Global-initiative-combining-forces-to-end-routine-gasflaring.html
dc.identifier.citationThe World Bank. (2016). Global Gas Flaring Reduction. World Bank Group. Washington. Recuperado de http://documents.worldbank.org/curated/en/590561468765565919/pdf/295540Regulati1aring0 no10301public1.pdf
dc.identifier.citationTing, C. J., & Chen, C. H. (2013). A multiple ant colony optimization algorithm for the capacitated location routing problem. International Journal of Production Economics, 141(1), 34–44.
dc.identifier.citationTunalıoğlu, R., Koç, Ç., & Bektaş, T. (2016). A multiperiod location-routing problem arising in the collection of Olive Oil Mill Wastewater. Journal of the Operational Research Society, 67(7), 1–13
dc.identifier.citationUnidad de Planeación Minero Energética. (2015a). Plan energetico nacional colombia : ideario energético 2050. Bogotá. Recuperado de http://www.upme.gov.co/docs/pen/pen_idearioenergetico2050.pdf
dc.identifier.citationUnidad de Planeación Minero Energética. (2015b). Plan Indicativo de Abastecimiento de Gas Natural. Recuperado de http://www1.upme.gov.co/sites/default/files/Plan_Indicativo_Gas_Natural_2015.pdf
dc.identifier.citationUnidad de Planeación Minero Energética. (2016). Consulta Series de Tiempo. Recuperado March 21, 2017, de http://www.upme.gov.co/generadorconsultas/Consulta_Series.aspx?idModulo=3&tipoSerie=1 38
dc.identifier.citationUnited States Energy Information Administration. (2016). Trends in US Oil and Natural Gas Upstream Costs
dc.identifier.citationUniversidad Nacional de Colombia. Grupo de Investigación en Geofísica., J. G., Guerrero, J. G., Vargas, C. A., & Montes, L. (2010). Earth sciences research journal. Earth Sciences Research Journal (Vol. 14). Universidad Nacional de Colombia, Facultad de Ciencias, Departamento de Geociencías, Grupo de Investigación en Geofísica.
dc.identifier.citationVenkata Narasimha, K., Kivelevitch, E., Sharma, B., & Kumar, M. (2013). An ant colony optimization technique for solving min-max Multi-Depot Vehicle Routing Problem. Swarm and Evolutionary Computation, 13, 63–73.
dc.identifier.citationWood, D. A. (2016). Evolutionary memetic algorithms supported by metaheuristic profiling effectively applied to the optimization of discrete routing problems. Journal of Natural Gas Science and Engineering, 35, 997–1014.
dc.identifier.citationYildiz, B., Arslan, O., & Karaşan, O. E. (2016). A branch and price approach for routing and refueling station location model. European Journal of Operational Research, 248(3), 815– 826.
dc.identifier.citationYou, P. S., & Hsieh, Y. C. (2012). A heuristic approach to a single stage assembly problem with transportation allocation. Applied Mathematics and Computation, 218(22), 11100–11111.
dc.identifier.citationYu, V. F., Lin, S. W., Lee, W., & Ting, C. J. (2010). A simulated annealing heuristic for the capacitated location routing problem. Computers and Industrial Engineering, 58(2), 288–299.
dc.identifier.citationZhang, J., Zhao, Y., Xue, W., & Li, J. (2015). Vehicle routing problem with fuel consumption and carbon emission. International Journal of Production Economics, 170, 234–242.
dc.identifier.citationZhao, J., & Verter, V. (2015). A bi-objective model for the used oil location-routing problem. Computers and Operations Research, 62, 157–168.
dc.identifier.urihttp://hdl.handle.net/10818/33079
dc.descriptionsssses_CO
dc.description.abstractEl Gas Asociado al Petróleo (GAP) presente durante la extracción del petróleo es un gas combustible con uso industrial. Sin embargo, debido a su bajo valor comercial y bajos volúmenes de producción no es atractivo dentro de los campos donde se explota el petróleo crudo, por esta razón es común encontrar campos petroleros en donde este gas es quemado o simplemente liberado al ambiente, lo cual conlleva a un no aprovechamiento del recurso y un problema ambiental Rajović, Kiss, Maravić, y Bera, (2016). El actual auge ambientalista ha impulsado el interés de los grandes productores respecto al desarrollo de nuevos métodos para disminuir el impacto generado por el GAP, prueba de esto son los avances en sistemas de captación y utilización de este recurso. A pesar de esto, el costo del transporte ha sido limitante de la viabilidad de muchos proyectos relacionados. No obstante, mediante la aplicación de herramientas logísticas es posible determinar la localización de plantas de procesamiento o transformación de GAP dentro de los campos petroleros y diseñar redes de transporte vehicular que permitan conectar los puntos de producción con esos centros de utilización o transformación de este recurso. (Rodina, 2016) Dado que la industria petrolera es hasta el momento el principal pilar de la economía colombiana, es fácil encontrar ejemplos de quema y liberación de GAP en los campos petroleros del país. De acuerdo con información del Seminario Regional del Gas de 2015 realizado por el BANCO MUNDIAL (The World Bank, 2015), se estima que durante el periodo comprendido entre los años 1995 y 2006, en Colombia se quemaron al año en promedio 0,4 Billones de Metros Cúbicos (BMC) de GAP. En adición, mediante información satelital se determinó que la mayor concentración de Teas (antorchas que queman el gas) en Colombia se encuentra en los campos del Meta y Casanare aportando el 50% del gas quemado nacion.es_CO
dc.formatapplication/pdfes_CO
dc.language.isospaes_CO
dc.publisherUniversidad de La Sabanaes_CO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceUniversidad de La Sabana
dc.sourceIntellectum Repositorio Universidad de La Sabana
dc.subjectIndustria y comercio del petróleoes_CO
dc.subjectGas natural
dc.subjectGas natural -- Transporte
dc.subjectGas -- Obtención y producción
dc.titleModelo de localización y ruteo para el transporte del gas asociado a la producción de crudo en campos petroleroses_CO
dc.typemasterThesises_CO
dc.publisher.programMaestría en Gerencia de Operacioneses_CO
dc.publisher.departmentEscuela Internacional de Ciencias Económicas y Administrativases_CO
dc.identifier.local268717
dc.identifier.localTE09664
dc.type.hasVersionpublishedVersiones_CO
dc.rights.accessRightsrestrictedAccesses_CO
dc.creator.degreeMagíster en Gerencia de Operacioneses_CO


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