A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation

Solve a strategic operational problem for a company, requires mathematical modeling and computing power, therefore, it requires computational tools that contribute to decision support system (DSS). The development for the suboptimal planning and distribution of freight vehicles in its logistics netw...

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Autores:
Castro-Bolaño, Lauren J.
Uribe-Martes, Carlos J.
Coronado-Hernandez, Jairo R.
Ramírez-Ríos, Diana G.
Herazo-Padilla, Nilson
Paez-Logreira, Hayder
Gatica, Gustavo
Tipo de recurso:
Article of investigation
Fecha de publicación:
2021
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/10859
Acceso en línea:
https://hdl.handle.net/11323/10859
https://repositorio.cuc.edu.co
Palabra clave:
Decision support system
Heuristics
Large-scale optimization
Metaheuristics
Urban freight transportation
Vehicle routing problem
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
id RCUC2_6cf2f0fc0b0ef888d7e07672644fed92
oai_identifier_str oai:repositorio.cuc.edu.co:11323/10859
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.eng.fl_str_mv A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
title A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
spellingShingle A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
Decision support system
Heuristics
Large-scale optimization
Metaheuristics
Urban freight transportation
Vehicle routing problem
title_short A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
title_full A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
title_fullStr A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
title_full_unstemmed A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
title_sort A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation
dc.creator.fl_str_mv Castro-Bolaño, Lauren J.
Uribe-Martes, Carlos J.
Coronado-Hernandez, Jairo R.
Ramírez-Ríos, Diana G.
Herazo-Padilla, Nilson
Paez-Logreira, Hayder
Gatica, Gustavo
dc.contributor.author.none.fl_str_mv Castro-Bolaño, Lauren J.
Uribe-Martes, Carlos J.
Coronado-Hernandez, Jairo R.
Ramírez-Ríos, Diana G.
Herazo-Padilla, Nilson
Paez-Logreira, Hayder
Gatica, Gustavo
dc.subject.proposal.eng.fl_str_mv Decision support system
Heuristics
Large-scale optimization
Metaheuristics
Urban freight transportation
Vehicle routing problem
topic Decision support system
Heuristics
Large-scale optimization
Metaheuristics
Urban freight transportation
Vehicle routing problem
description Solve a strategic operational problem for a company, requires mathematical modeling and computing power, therefore, it requires computational tools that contribute to decision support system (DSS). The development for the suboptimal planning and distribution of freight vehicles in its logistics network is presented. It is considered contributing to two problems NP-Hard, the allocation (strategic) and routing of vehicles with time intervals for deliveries to the customer locations (operative, known as VRPTW) in order to minimize the total travel time and cost of the logistics operation, with capacity restrictions and client’s time intervals for deliveries. Furthermore, the research considers data obtained from real scenarios, which is why they are classified as combinatorial problems on a large scale. The logistics problem involved in urban freight transportation is approached as a VRPTW, where several optimization algorithms are used to solve sub-models of the mayor complex model, resulting in hybrid solution approach that involves metaheuristics and heuristics. By using the Snow methodology, which considers cases of a company, a web-based application is developed, such as a successful DSS, which allows suboptimal solution to large-scale problems and the improvement in the urban freight logistic problem in a city of Colombia.
publishDate 2021
dc.date.issued.none.fl_str_mv 2021
dc.date.accessioned.none.fl_str_mv 2024-03-18T15:02:55Z
dc.date.available.none.fl_str_mv 2024-03-18T15:02:55Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.content.spa.fl_str_mv Text
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dc.identifier.citation.spa.fl_str_mv Castro-Bolaño, L. J., Uribe-Martes, C. J., Coronado-Hernandez, J. R., Ramírez-Ríos, D. G., Herazo-Padilla, N., Paez-Logreira, H., & Gatica, G. (2021). A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2021(E44), 464–472.
dc.identifier.issn.spa.fl_str_mv 1646-9895
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/11323/10859
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co
identifier_str_mv Castro-Bolaño, L. J., Uribe-Martes, C. J., Coronado-Hernandez, J. R., Ramírez-Ríos, D. G., Herazo-Padilla, N., Paez-Logreira, H., & Gatica, G. (2021). A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2021(E44), 464–472.
1646-9895
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/10859
https://repositorio.cuc.edu.co
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.ispartofjournal.spa.fl_str_mv RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao
dc.relation.references.spa.fl_str_mv Ballou, R. H. (2004). Logística: administración de la cadena de suministro. https://books.google.com/books?hl=es&lr=&id=ii5xqLQ5VLgC&pgis=1
Bard, J. F., Kontoravdis, G., & Yu, G. (2002). A Branch-and-Cut Procedure for the Vehicle Routing Problem with Time Windows. Transportation Science, 36(2), 250–269. https://doi.org/10.1287/trsc.36.2.250.565
Bodin, L., Golden, B., Assad, A., & Ball, M. (1981). The state of the art in the routing and scheduling of vehicles and crews. https://trid.trb.org/view/171165
Cattaruzza, D., Absi, N., Feillet, D., & González-Feliu, J. (2017). Vehicle routing problems for city logistics. EURO Journal on Transportation and Logistics, 6(1), 51–79. https://doi.org/10.1007/s13676-014-0074-0
Chrissis, M. B., Konrad, M., & Shrum, S. (2011). CMMI ® Second Edition: Guidelines for Process Integration and Product Improvement. In SEI Series in Software Engineering. Pearson Education. https://doi.org/0321711505
Crainic, T. G., Errico, F., Rei, W., & Ricciardi, N. (2016). Modeling Demand Uncertainty in Two-Tier City Logistics Tactical Planning. Transportation Science, 50(2), 363–761. https://doi.org/10.1287/trsc.2015.0606
Dablanc, L. (2007). Goods transport in large European cities: Difficult to organize, difficult to modernize. Transportation Research Part A: Policy and Practice, 41(3), 280–285. https://doi.org/10.1016/J.TRA.2006.05.005
Gambardella, L., Taillard, É., & Agazzi, G. (1999). MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. In New Ideas in Optimization (pp. 63-76.). McGraw-Hill’s. https://doi.org/10.1.1.45.5381
Garcia-Najera, A., & Bullinaria, J. A. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287–300. https://doi.org/10.1016/J.COR.2010.05.004
Gendreau, M., Guertin, F., Potvin, J.-Y., & Taillard, É. (1999). Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching. Transportation Science, 33(4), 381–390. https://doi.org/10.1287/trsc.33.4.381
Hesse, M., & Rodrigue, J.-P. (2004). The transport geography of logistics and freight distribution. Journal of Transport Geography, 12(3), 171–184. https://doi.org/10.1016/J.JTRANGEO.2003.12.004
Holguín-Veras, J., Encarnación, T., González-Calderón, C. A., Winebrake, J., Kyle, S., Herazo-Padilla, N., Kalahasthi, L., Adarme, W., Cantillo, V., Yoshizaki, H., & Garrido, R. (2018). Direct impacts of off-hour deliveries on urban freight emissions.Transportation Research Part D: Transport and Environment, 61, 84–103. https://doi.org/10.1016/J.TRD.2016.10.013
Jacobson, I. (1992). Object-oriented software engineering : a use case driven approach. ACM Press.
Maropoulos, P. G., & Ceglarek, D. (2010). Design verification and validation in product lifecycle. CIRP Annals, 59(2), 740–759. https://doi.org/10.1016/J. CIRP.2010.05.005
Masrom, S., Abidin, S. Z. Z., Omar, N., Nasir, K., & Abd Rahman, A. S. (2015). Dynamic parameterization of the particle swarm optimization and genetic algorithm hybrids for vehicle routing problem with time window. International Journal of Hybrid Intelligent Systems, 12(1), 13–25. https://doi.org/10.3233/HIS-140202
Pecin, D., Contardo, C., Desaulniers, G., & Uchoa, E. (2017). New Enhancements for the Exact Solution of the Vehicle Routing Problem with Time Windows. INFORMS Journal on Computing, 29(3), 489–502. https://doi.org/10.1287/ijoc.2016.0744
Saeheaw, T., & Charoenchai, N. (2016). Comparison of Meta-heuristic Algorithms for Vehicle Routing Problem with Time Windows (pp. 1263–1273). Springer, Cham. https://doi.org/10.1007/978-3-319-24584-3_108
Sánchez-Dams, R. (2014). Metodología ágil estandarizada para el desarrollo o ejecución de proyectos de sistemas embebidos. Universidad del Norte.
Vigo, D., & Toth, P. (2014). Vehicle Routing; Problems, Methods, and Applications. In MOS-SIAM Series on Optimization. https://doi.org/doi:10.1137/1.9781611973594
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dc.relation.citationstartpage.spa.fl_str_mv 464
dc.relation.citationvolume.spa.fl_str_mv 2021
dc.rights.eng.fl_str_mv Copyright 2022 Elsevier B.V., All rights reserved.
dc.rights.license.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0)Copyright 2022 Elsevier B.V., All rights reserved.https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Castro-Bolaño, Lauren J.Uribe-Martes, Carlos J.Coronado-Hernandez, Jairo R.Ramírez-Ríos, Diana G.Herazo-Padilla, NilsonPaez-Logreira, HayderGatica, Gustavo2024-03-18T15:02:55Z2024-03-18T15:02:55Z2021Castro-Bolaño, L. J., Uribe-Martes, C. J., Coronado-Hernandez, J. R., Ramírez-Ríos, D. G., Herazo-Padilla, N., Paez-Logreira, H., & Gatica, G. (2021). A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation. RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2021(E44), 464–472.1646-9895https://hdl.handle.net/11323/10859Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.coSolve a strategic operational problem for a company, requires mathematical modeling and computing power, therefore, it requires computational tools that contribute to decision support system (DSS). The development for the suboptimal planning and distribution of freight vehicles in its logistics network is presented. It is considered contributing to two problems NP-Hard, the allocation (strategic) and routing of vehicles with time intervals for deliveries to the customer locations (operative, known as VRPTW) in order to minimize the total travel time and cost of the logistics operation, with capacity restrictions and client’s time intervals for deliveries. Furthermore, the research considers data obtained from real scenarios, which is why they are classified as combinatorial problems on a large scale. The logistics problem involved in urban freight transportation is approached as a VRPTW, where several optimization algorithms are used to solve sub-models of the mayor complex model, resulting in hybrid solution approach that involves metaheuristics and heuristics. By using the Snow methodology, which considers cases of a company, a web-based application is developed, such as a successful DSS, which allows suboptimal solution to large-scale problems and the improvement in the urban freight logistic problem in a city of Colombia.10 páginasapplication/pdfengAssociacao Iberica de Sistemas e Tecnologias de Informacao (AISTI)Portugalhttps://www.scopus.com/record/display.uri?eid=2-s2.0-85134054221&origin=inward&txGid=d4decae29412bee53096675a94be9969A Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportationArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85RISTI - Revista Iberica de Sistemas e Tecnologias de InformacaoBallou, R. H. (2004). Logística: administración de la cadena de suministro. https://books.google.com/books?hl=es&lr=&id=ii5xqLQ5VLgC&pgis=1Bard, J. F., Kontoravdis, G., & Yu, G. (2002). A Branch-and-Cut Procedure for the Vehicle Routing Problem with Time Windows. Transportation Science, 36(2), 250–269. https://doi.org/10.1287/trsc.36.2.250.565Bodin, L., Golden, B., Assad, A., & Ball, M. (1981). The state of the art in the routing and scheduling of vehicles and crews. https://trid.trb.org/view/171165Cattaruzza, D., Absi, N., Feillet, D., & González-Feliu, J. (2017). Vehicle routing problems for city logistics. EURO Journal on Transportation and Logistics, 6(1), 51–79. https://doi.org/10.1007/s13676-014-0074-0Chrissis, M. B., Konrad, M., & Shrum, S. (2011). CMMI ® Second Edition: Guidelines for Process Integration and Product Improvement. In SEI Series in Software Engineering. Pearson Education. https://doi.org/0321711505Crainic, T. G., Errico, F., Rei, W., & Ricciardi, N. (2016). Modeling Demand Uncertainty in Two-Tier City Logistics Tactical Planning. Transportation Science, 50(2), 363–761. https://doi.org/10.1287/trsc.2015.0606Dablanc, L. (2007). Goods transport in large European cities: Difficult to organize, difficult to modernize. Transportation Research Part A: Policy and Practice, 41(3), 280–285. https://doi.org/10.1016/J.TRA.2006.05.005Gambardella, L., Taillard, É., & Agazzi, G. (1999). MACS-VRPTW: A Multiple Ant Colony System for Vehicle Routing Problems with Time Windows. In New Ideas in Optimization (pp. 63-76.). McGraw-Hill’s. https://doi.org/10.1.1.45.5381Garcia-Najera, A., & Bullinaria, J. A. (2011). An improved multi-objective evolutionary algorithm for the vehicle routing problem with time windows. Computers & Operations Research, 38(1), 287–300. https://doi.org/10.1016/J.COR.2010.05.004Gendreau, M., Guertin, F., Potvin, J.-Y., & Taillard, É. (1999). Parallel Tabu Search for Real-Time Vehicle Routing and Dispatching. Transportation Science, 33(4), 381–390. https://doi.org/10.1287/trsc.33.4.381Hesse, M., & Rodrigue, J.-P. (2004). The transport geography of logistics and freight distribution. Journal of Transport Geography, 12(3), 171–184. https://doi.org/10.1016/J.JTRANGEO.2003.12.004Holguín-Veras, J., Encarnación, T., González-Calderón, C. A., Winebrake, J., Kyle, S., Herazo-Padilla, N., Kalahasthi, L., Adarme, W., Cantillo, V., Yoshizaki, H., & Garrido, R. (2018). Direct impacts of off-hour deliveries on urban freight emissions.Transportation Research Part D: Transport and Environment, 61, 84–103. https://doi.org/10.1016/J.TRD.2016.10.013Jacobson, I. (1992). Object-oriented software engineering : a use case driven approach. ACM Press.Maropoulos, P. G., & Ceglarek, D. (2010). Design verification and validation in product lifecycle. CIRP Annals, 59(2), 740–759. https://doi.org/10.1016/J. CIRP.2010.05.005Masrom, S., Abidin, S. Z. Z., Omar, N., Nasir, K., & Abd Rahman, A. S. (2015). Dynamic parameterization of the particle swarm optimization and genetic algorithm hybrids for vehicle routing problem with time window. International Journal of Hybrid Intelligent Systems, 12(1), 13–25. https://doi.org/10.3233/HIS-140202Pecin, D., Contardo, C., Desaulniers, G., & Uchoa, E. (2017). New Enhancements for the Exact Solution of the Vehicle Routing Problem with Time Windows. INFORMS Journal on Computing, 29(3), 489–502. https://doi.org/10.1287/ijoc.2016.0744Saeheaw, T., & Charoenchai, N. (2016). Comparison of Meta-heuristic Algorithms for Vehicle Routing Problem with Time Windows (pp. 1263–1273). Springer, Cham. https://doi.org/10.1007/978-3-319-24584-3_108Sánchez-Dams, R. (2014). Metodología ágil estandarizada para el desarrollo o ejecución de proyectos de sistemas embebidos. Universidad del Norte.Vigo, D., & Toth, P. (2014). Vehicle Routing; Problems, Methods, and Applications. In MOS-SIAM Series on Optimization. https://doi.org/doi:10.1137/1.97816119735944724642021Decision support systemHeuristicsLarge-scale optimizationMetaheuristicsUrban freight transportationVehicle routing problemPublicationORIGINALA Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation.pdfA Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation.pdfArtículoapplication/pdf337294https://repositorio.cuc.edu.co/bitstreams/185b9329-bf01-4df2-bfb6-76291cf901ad/download4956cdc5e63a15b1f079419ec86df413MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-814828https://repositorio.cuc.edu.co/bitstreams/e0761aba-070a-4e1b-a7cf-6dd1604e5f8f/download2f9959eaf5b71fae44bbf9ec84150c7aMD52TEXTA Decision Support System (DSS) for the heuristic allocation and routing of vehicles in urban freight transportation.pdf.txtA Decision Support System (DSS) for the heuristic allocation and 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ada en las Obras Colectivas.

b.	Distribuir copias o fonogramas de las Obras, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública, incluyéndolas como incorporadas en Obras Colectivas, según corresponda.

c.	Distribuir copias de las Obras Derivadas que se generen, exhibirlas públicamente, ejecutarlas públicamente y/o ponerlas a disposición pública.
Los derechos mencionados anteriormente pueden ser ejercidos en todos los medios y formatos, actualmente conocidos o que se inventen en el futuro. Los derechos antes mencionados incluyen el derecho a realizar dichas modificaciones en la medida que sean técnicamente necesarias para ejercer los derechos en otro medio o formatos, pero de otra manera usted no está autorizado para realizar obras derivadas. Todos los derechos no otorgados expresamente por el Licenciante quedan por este medio reservados, incluyendo pero sin limitarse a aquellos que se mencionan en las secciones 4(d) y 4(e).

4. Restricciones.
La licencia otorgada en la anterior Sección 3 está expresamente sujeta y limitada por las siguientes restricciones:

a.	Usted puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra sólo bajo las condiciones de esta Licencia, y Usted debe incluir una copia de esta licencia o del Identificador Universal de Recursos de la misma con cada copia de la Obra que distribuya, exhiba públicamente, ejecute públicamente o ponga a disposición pública. No es posible ofrecer o imponer ninguna condición sobre la Obra que altere o limite las condiciones de esta Licencia o el ejercicio de los derechos de los destinatarios otorgados en este documento. No es posible sublicenciar la Obra. Usted debe mantener intactos todos los avisos que hagan referencia a esta Licencia y a la cláusula de limitación de garantías. Usted no puede distribuir, exhibir públicamente, ejecutar públicamente, o poner a disposición pública la Obra con alguna medida tecnológica que controle el acceso o la utilización de ella de una forma que sea inconsistente con las condiciones de esta Licencia. Lo anterior se aplica a la Obra incorporada a una Obra Colectiva, pero esto no exige que la Obra Colectiva aparte de la obra misma quede sujeta a las condiciones de esta Licencia. Si Usted crea una Obra Colectiva, previo aviso de cualquier Licenciante debe, en la medida de lo posible, eliminar de la Obra Colectiva cualquier referencia a dicho Licenciante o al Autor Original, según lo solicitado por el Licenciante y conforme lo exige la cláusula 4(c).

b.	Usted no puede ejercer ninguno de los derechos que le han sido otorgados en la Sección 3 precedente de modo que estén principalmente destinados o directamente dirigidos a conseguir un provecho comercial o una compensación monetaria privada. El intercambio de la Obra por otras obras protegidas por derechos de autor, ya sea a través de un sistema para compartir archivos digitales (digital file-sharing) o de cualquier otra manera no será considerado como estar destinado principalmente o dirigido directamente a conseguir un provecho comercial o una compensación monetaria privada, siempre que no se realice un pago mediante una compensación monetaria en relación con el intercambio de obras protegidas por el derecho de autor.

c.	Si usted distribuye, exhibe públicamente, ejecuta públicamente o ejecuta públicamente en forma digital la Obra o cualquier Obra Derivada u Obra Colectiva, Usted debe mantener intacta toda la información de derecho de autor de la Obra y proporcionar, de forma razonable según el medio o manera que Usted esté utilizando: (i) el nombre del Autor Original si está provisto (o seudónimo, si fuere aplicable), y/o (ii) el nombre de la parte o las partes que el Autor Original y/o el Licenciante hubieren designado para la atribución (v.g., un instituto patrocinador, editorial, publicación) en la información de los derechos de autor del Licenciante, términos de servicios o de otras formas razonables; el título de la Obra si está provisto; en la medida de lo razonablemente factible y, si está provisto, el Identificador Uniforme de Recursos (Uniform Resource Identifier) que el Licenciante especifica para ser asociado con la Obra, salvo que tal URI no se refiera a la nota sobre los derechos de autor o a la información sobre el licenciamiento de la Obra; y en el caso de una Obra Derivada, atribuir el crédito identificando el uso de la Obra en la Obra Derivada (v.g., "Traducción Francesa de la Obra del Autor Original," o "Guión Cinematográfico basado en la Obra original del Autor Original"). Tal crédito puede ser implementado de cualquier forma razonable; en el caso, sin embargo, de Obras Derivadas u Obras Colectivas, tal crédito aparecerá, como mínimo, donde aparece el crédito de cualquier otro autor comparable y de una manera, al menos, tan destacada como el crédito de otro autor comparable.

d.	Para evitar toda confusión, el Licenciante aclara que, cuando la obra es una composición musical:

i.	Regalías por interpretación y ejecución bajo licencias generales. El Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública o la ejecución pública digital de la obra y de recolectar, sea individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, SAYCO), las regalías por la ejecución pública o por la ejecución pública digital de la obra (por ejemplo Webcast) licenciada bajo licencias generales, si la interpretación o ejecución de la obra está primordialmente orientada por o dirigida a la obtención de una ventaja comercial o una compensación monetaria privada.

ii.	Regalías por Fonogramas. El Licenciante se reserva el derecho exclusivo de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, los consagrados por la SAYCO), una agencia de derechos musicales o algún agente designado, las regalías por cualquier fonograma que Usted cree a partir de la obra (“versión cover”) y distribuya, en los términos del régimen de derechos de autor, si la creación o distribución de esa versión cover está primordialmente destinada o dirigida a obtener una ventaja comercial o una compensación monetaria privada.

e.	Gestión de Derechos de Autor sobre Interpretaciones y Ejecuciones Digitales (WebCasting). Para evitar toda confusión, el Licenciante aclara que, cuando la obra sea un fonograma, el Licenciante se reserva el derecho exclusivo de autorizar la ejecución pública digital de la obra (por ejemplo, webcast) y de recolectar, individualmente o a través de una sociedad de gestión colectiva de derechos de autor y derechos conexos (por ejemplo, ACINPRO), las regalías por la ejecución pública digital de la obra (por ejemplo, webcast), sujeta a las disposiciones aplicables del régimen de Derecho de Autor, si esta ejecución pública digital está primordialmente dirigida a obtener una ventaja comercial o una compensación monetaria privada.

5. Representaciones, Garantías y Limitaciones de Responsabilidad.
A MENOS QUE LAS PARTES LO ACORDARAN DE OTRA FORMA POR ESCRITO, EL LICENCIANTE OFRECE LA OBRA (EN EL ESTADO EN EL QUE SE ENCUENTRA) “TAL CUAL”, SIN BRINDAR GARANTÍAS DE CLASE ALGUNA RESPECTO DE LA OBRA, YA SEA EXPRESA, IMPLÍCITA, LEGAL O CUALQUIERA OTRA, INCLUYENDO, SIN LIMITARSE A ELLAS, GARANTÍAS DE TITULARIDAD, COMERCIABILIDAD, ADAPTABILIDAD O ADECUACIÓN A PROPÓSITO DETERMINADO, AUSENCIA DE INFRACCIÓN, DE AUSENCIA DE DEFECTOS LATENTES O DE OTRO TIPO, O LA PRESENCIA O AUSENCIA DE ERRORES, SEAN O NO DESCUBRIBLES (PUEDAN O NO SER ESTOS DESCUBIERTOS). ALGUNAS JURISDICCIONES NO PERMITEN LA EXCLUSIÓN DE GARANTÍAS IMPLÍCITAS, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

6. Limitación de responsabilidad.
A MENOS QUE LO EXIJA EXPRESAMENTE LA LEY APLICABLE, EL LICENCIANTE NO SERÁ RESPONSABLE ANTE USTED POR DAÑO ALGUNO, SEA POR RESPONSABILIDAD EXTRACONTRACTUAL, PRECONTRACTUAL O CONTRACTUAL, OBJETIVA O SUBJETIVA, SE TRATE DE DAÑOS MORALES O PATRIMONIALES, DIRECTOS O INDIRECTOS, PREVISTOS O IMPREVISTOS PRODUCIDOS POR EL USO DE ESTA LICENCIA O DE LA OBRA, AUN CUANDO EL LICENCIANTE HAYA SIDO ADVERTIDO DE LA POSIBILIDAD DE DICHOS DAÑOS. ALGUNAS LEYES NO PERMITEN LA EXCLUSIÓN DE CIERTA RESPONSABILIDAD, EN CUYO CASO ESTA EXCLUSIÓN PUEDE NO APLICARSE A USTED.

7. Término.

a.	Esta Licencia y los derechos otorgados en virtud de ella terminarán automáticamente si Usted infringe alguna condición establecida en ella. Sin embargo, los individuos o entidades que han recibido Obras Derivadas o Colectivas de Usted de conformidad con esta Licencia, no verán terminadas sus licencias, siempre que estos individuos o entidades sigan cumpliendo íntegramente las condiciones de estas licencias. Las Secciones 1, 2, 5, 6, 7, y 8 subsistirán a cualquier terminación de esta Licencia.

b.	Sujeta a las condiciones y términos anteriores, la licencia otorgada aquí es perpetua (durante el período de vigencia de los derechos de autor de la obra). No obstante lo anterior, el Licenciante se reserva el derecho a publicar y/o estrenar la Obra bajo condiciones de licencia diferentes o a dejar de distribuirla en los términos de esta Licencia en cualquier momento; en el entendido, sin embargo, que esa elección no servirá para revocar esta licencia o que deba ser otorgada , bajo los términos de esta licencia), y esta licencia continuará en pleno vigor y efecto a menos que sea terminada como se expresa atrás. La Licencia revocada continuará siendo plenamente vigente y efectiva si no se le da término en las condiciones indicadas anteriormente.

8. Varios.

a.	Cada vez que Usted distribuya o ponga a disposición pública la Obra o una Obra Colectiva, el Licenciante ofrecerá al destinatario una licencia en los mismos términos y condiciones que la licencia otorgada a Usted bajo esta Licencia.

b.	Si alguna disposición de esta Licencia resulta invalidada o no exigible, según la legislación vigente, esto no afectará ni la validez ni la aplicabilidad del resto de condiciones de esta Licencia y, sin acción adicional por parte de los sujetos de este acuerdo, aquélla se entenderá reformada lo mínimo necesario para hacer que dicha disposición sea válida y exigible.

c.	Ningún término o disposición de esta Licencia se estimará renunciada y ninguna violación de ella será consentida a menos que esa renuncia o consentimiento sea otorgado por escrito y firmado por la parte que renuncie o consienta.

d.	Esta Licencia refleja el acuerdo pleno entre las partes respecto a la Obra aquí licenciada. No hay arreglos, acuerdos o declaraciones respecto a la Obra que no estén especificados en este documento. El Licenciante no se verá limitado por ninguna disposición adicional que pueda surgir en alguna comunicación emanada de Usted. Esta Licencia no puede ser modificada sin el consentimiento mutuo por escrito del Licenciante y Usted.
