Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks
The paper examines a proposal on scheduling repair resources to deal with temporary road disruptions in humanitarian aid networks. A mathematical model was formulated, which took minimizing the total time of completion of the repair, as well as the arrival and departure times of crews and repair tea...
- Autores:
-
Rojas Trejos, Carlos Alberto
Meisel, Jose D.
Adarme-Jaimes, Wilson
Orejuela Cabrera, Juan Pablo
- Tipo de recurso:
- Article of investigation
- Fecha de publicación:
- 2025
- Institución:
- Universidad de Ibagué
- Repositorio:
- Repositorio Universidad de Ibagué
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unibague.edu.co:20.500.12313/6063
- Acceso en línea:
- https://hdl.handle.net/20.500.12313/6063
https://www.sciencedirect.com/science/article/pii/S0360835225001664
- Palabra clave:
- Interrupciones viales transitorias - Redes de ayuda humanitaria
Access restoration
Humanitarian logistics
Mathematical model
Repair scheduling
- Rights
- closedAccess
- License
- © 2025 The Author(s)
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Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| title |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| spellingShingle |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks Interrupciones viales transitorias - Redes de ayuda humanitaria Access restoration Humanitarian logistics Mathematical model Repair scheduling |
| title_short |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| title_full |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| title_fullStr |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| title_full_unstemmed |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| title_sort |
Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks |
| dc.creator.fl_str_mv |
Rojas Trejos, Carlos Alberto Meisel, Jose D. Adarme-Jaimes, Wilson Orejuela Cabrera, Juan Pablo |
| dc.contributor.author.none.fl_str_mv |
Rojas Trejos, Carlos Alberto Meisel, Jose D. Adarme-Jaimes, Wilson Orejuela Cabrera, Juan Pablo |
| dc.subject.armarc.none.fl_str_mv |
Interrupciones viales transitorias - Redes de ayuda humanitaria |
| topic |
Interrupciones viales transitorias - Redes de ayuda humanitaria Access restoration Humanitarian logistics Mathematical model Repair scheduling |
| dc.subject.proposal.eng.fl_str_mv |
Access restoration Humanitarian logistics Mathematical model Repair scheduling |
| description |
The paper examines a proposal on scheduling repair resources to deal with temporary road disruptions in humanitarian aid networks. A mathematical model was formulated, which took minimizing the total time of completion of the repair, as well as the arrival and departure times of crews and repair teams, and relations of precedence and complementarity between resources and the availability of resources into consideration. To validate the model, a real case study was used, where a region is presented, which has been affected by floods that generate temporary road disruptions. Finally, a scenario analysis of the model was performed so that the impact on performance related to the variation of parameters of interest, such as the availability of resources, the repair times of the crews, the machine operating times and the expected restoration completion time can be studied. The results showed that the impact on the scheduling of repair resources and the total repair time depends on the required conditions of the roads that are going to be repaired, interdependence, and resources availability. However, the findings indicated that increases beyond resource availability have no effect on the total completion time. Better results can be achieved in total completion time if arrival and completion times of available resources are properly synchronized. This research is a contribution on the importance of relations of precedence in the scheduling for road repair, the interdependence of resources and the special conditions of allocation between crews and type of machinery according to the affected track, and its impact on the completion times of the repair. |
| publishDate |
2025 |
| dc.date.accessioned.none.fl_str_mv |
2025-11-28T22:46:06Z |
| dc.date.available.none.fl_str_mv |
2025-11-28T22:46:06Z |
| dc.date.issued.none.fl_str_mv |
2025-05 |
| dc.type.none.fl_str_mv |
Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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Text |
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Rojas Trejos, Carlos Alberto., Meisel, Jose D., Adarme-Jaimes, Wilson. y Orejuela Cabrera, Juan Pablo. (2025). Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks. Computers and Industrial Engineering, 203. DOI: 10.1016/j.cie.2025.111020 |
| dc.identifier.doi.none.fl_str_mv |
10.1016/j.cie.2025.111020 |
| dc.identifier.issn.none.fl_str_mv |
03608352 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12313/6063 |
| dc.identifier.url.none.fl_str_mv |
https://www.sciencedirect.com/science/article/pii/S0360835225001664 |
| identifier_str_mv |
Rojas Trejos, Carlos Alberto., Meisel, Jose D., Adarme-Jaimes, Wilson. y Orejuela Cabrera, Juan Pablo. (2025). Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks. Computers and Industrial Engineering, 203. DOI: 10.1016/j.cie.2025.111020 10.1016/j.cie.2025.111020 03608352 |
| url |
https://hdl.handle.net/20.500.12313/6063 https://www.sciencedirect.com/science/article/pii/S0360835225001664 |
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eng |
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eng |
| dc.relation.citationvolume.none.fl_str_mv |
203 |
| dc.relation.ispartofjournal.none.fl_str_mv |
Computers and Industrial Engineering |
| dc.relation.references.none.fl_str_mv |
Aksu, D. T., & Ozdamar, L. (2014). A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation. Transportation Research Part ELogistics and Transportation Review, 61, 56–67. https://doi.org/10.1016/j. tre.2013.10.009 Alinaghian, M., Aghaie, M., & Sabbagh, M. S. (2019). A mathematical model for location of temporary relief centers and dynamic routing of aerial rescue vehicles. Computers and Industrial Engineering, 131(17), 227–241. https://doi.org/10.1016/j. cie.2019.03.002 Arif, A., Wang, Z., Chen, C., & Chen, B. (2020). A stochastic multi-commodity logistic model for disaster preparation in distribution systems. IEEE Transactions on Smart Grid, 11(1), 565–576. https://doi.org/10.1109/TSG.2019.2925620 Baxter, A. E., Wilborn Lagerman, H. E., & Keskinocak, P. (2020). Quantitative modeling in disaster management: A literature review. Retrieved from IBM Journal of Research and Development. https://www.scopus.com/inward/record.uri?eid=2-s2.0-850 81615488&doi=10.1147%2FJRD.2019.2960356&partnerID=40&md5=719517a 68324f26165a4852b4737e7c1 Çelik, M. (2016). Network restoration and recovery in humanitarian operations: Framework, literature review, and research directions. Surveys in Operations Research and Management Science, 21(2), 47–61. https://doi.org/10.1016/j. sorms.2016.12.001 Coco, A. A., Duhamel, C., & Santos, A. C. (2020). Modeling and solving the multi-period disruptions scheduling problem on urban networks. Annals of Operations Research, 285(1–2), 427–443. https://doi.org/10.1007/s10479-019-03248-5 Edrissi, A., Nourinejad, M., & Roorda, M. J. (2015). Transportation network reliability in emergency response. Transportation Research Part E: Logistics and Transportation Review, 80, 56–73. https://doi.org/10.1016/j.tre.2015.05.005 Habib, M. S., Lee, Y. H., & Memon, M. S. (2016). Mathematical models in humanitarian supply chain management: A systematic literature review. Mathematical Problems in Engineering, 2016. https://doi.org/10.1155/2016/3212095 Iloglu, S, & Albert, L. A. (2020). A maximal multiple coverage and network restoration problem for disaster recovery. Operations Research Perspectives. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85076843383&doi=10.1016%2Fj. orp.2019.100132&partnerID=40&md5=9e783fa41570f20ac3be34a824402d8b Iloglu, S., & Albert, L. A. (2018). An integrated network design and scheduling problem for network recovery and emergency response. Operations Research Perspectives, 5 (August), 218–231. https://doi.org/10.1016/j.orp.2018.08.001 Kim, S., Shin, Y., Lee, G. M., & Moon, I. (2018). Network repair crew scheduling for short-term disasters. Applied Mathematical Modelling, 64, 510. https://doi.org/10.101 6/j.apm.2018.07.047 Ibarra-Rojas, O. J., Hernandez, L., & Ozuna, L. (2018). The accessibility vehicle routing problem. Journal of Cleaner Production, 172, 1514–1528. https://doi.org/10.1016/j. jclepro.2017.10.249 Li, C., Fang, Q., Ding, L., Cho, Y. K., & Chen, K. (2020). Time-dependent resilience analysis of a road network in an extreme environment. Transportation Research Part D: Transport and Environment, 85. https://doi.org/10.1016/j.trd.2020.102395 Li, P., Lan, H., & Saldanha-Da-Gama, F. (2019). A Bi-objective capacitated locationrouting problem for multiple perishable commodities. IEEE Access, 7, 136729–136742. https://doi.org/10.1109/ACCESS.2019.2941363 Lu, G., Xiong, Y., Ding, C., & Wang, Y. (2016). An optimal schedule for urban road network repair based on the greedy algorithm. PLoS ONE, 11(10). https://doi.org/ 10.1371/journal.pone.0164780 Morshedlou, N., Barker, K., Nicholson, C. D., & Sansavini, G. (2018). Adaptive capacity planning formulation for infrastructure networks. Journal of Infrastructure Systems, 24(4). https://doi.org/10.1061/(ASCE)IS.1943-555X.0000432 Nurre, S. G., Cavdaroglu, B., Mitchell, J. E., Sharkey, T. C., & Wallace, W. A. (2012). Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem. European Journal of Operational Research, 223(3), 794–806. https:// doi.org/10.1016/j.ejor.2012.07.010 Reddy, G. H., Chakrapani, P., Goswami, A. K., & Choudhury, N. B. D. (2017). Fuzzy based approach for restoration of distribution system during post natural disasters. IEEE Access, 6, 3448–3458. https://doi.org/10.1109/ACCESS.2017.2779823 Rodriguez-Espindola, O., Albores, P., & Brewster, C. (2018). Dynamic formulation for humanitarian response operations incorporating multiple organisations. International Journal of Production Economics, 204(August), 83–98. https://doi.org/10.1016/j. ijpe.2018.07.023 Sakuraba, C S, Santos, A. C., Prins, C., Bouillot, L., Durand, A., & Allenbach, B. (2016). Road network emergency accessibility planning after a major earthquake. EURO Journal on Computational Optimization. Retrieved from https://www.scopus.com/ inward/record.uri?eid=2-s2.0-85027971781&doi=10.1007%2Fs13675-016-0070- 2&partnerID=40&md5=656f79f6c423468df965487bccfed969. Sanci, E., & Daskin, M. S. (2019). Integrating location and network restoration decisions in relief networks under uncertainty. European Journal of Operational Research, 279 (2), 335–350. https://doi.org/10.1016/j.ejor.2019.06.012 Shin, Y., Kim, S., & Moon, I. (2019). Integrated optimal scheduling of repair crew and relief vehicle after disaster. Computers and Operations Research, 105, 237–247. https://doi.org/10.1016/j.cor.2019.01.015 Vahdani, B., Veysmoradi, D., Shekari, N., & Mousavi, S. M. (2018). Multi-objective, multi-period location-routing model to distribute relief after earthquake by considering emergency roadway repair. Neural Computing and Applications, 30(3), 835–854. https://doi.org/10.1007/s00521-016-2696-7 Wu, J., & Wang, P. (2020). Post-disruption performance recovery to enhance resilience of interconnected network systems. Sustainable and Resilient Infrastructure. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85082017188&doi=10.1080%2F23789689.2019.1710073&partnerID=40 &md5=f4f461a1712f196f169974339afe5cf9. Yan, J., Hu, B., Xie, K., Tai, H. M., & Li, W. (2020). Post-disaster power system restoration planning considering sequence dependent repairing period. International Journal of Electrical Power and Energy Systems, 117. https://doi.org/10.1016/j. ijepes.2019.105612 Yan, S., & Shih, Y.-L. (2009). Optimal scheduling of emergency roadway repair and subsequent relief distribution. Computers and Operations Research, 36(6), 2049–2065. https://doi.org/10.1016/j.cor.2008.07.002 Zhang, Z., Wang, Z., & Zhou, H. (2020). An emergency resource allocation method based on supernetwork for urban disaster. Advances in Intelligent Systems and Computing, 1017, 248–255. https://doi.org/10.1007/978-3-030-25128-4_33 Zhou, Y., Liu, J., Zhang, Y., & Gan, X. (2017). A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems. Transportation Research Part E: Logistics and Transportation Review, 99, 77–95. https://doi. org/10.1016/j.tre.2016.12.011. |
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Rojas Trejos, Carlos Alberto5b67722a-42d2-4dec-8983-605e894bfb20-1Meisel, Jose D.fb6ee7e4-d71a-4ad0-ada1-224714cb0696-1Adarme-Jaimes, Wilson4638c849-3ee8-4896-9d69-63a4e7b1f10e-1Orejuela Cabrera, Juan Pablo32562675-4883-408c-a7c9-12f5e6cfa2c1-12025-11-28T22:46:06Z2025-11-28T22:46:06Z2025-05The paper examines a proposal on scheduling repair resources to deal with temporary road disruptions in humanitarian aid networks. A mathematical model was formulated, which took minimizing the total time of completion of the repair, as well as the arrival and departure times of crews and repair teams, and relations of precedence and complementarity between resources and the availability of resources into consideration. To validate the model, a real case study was used, where a region is presented, which has been affected by floods that generate temporary road disruptions. Finally, a scenario analysis of the model was performed so that the impact on performance related to the variation of parameters of interest, such as the availability of resources, the repair times of the crews, the machine operating times and the expected restoration completion time can be studied. The results showed that the impact on the scheduling of repair resources and the total repair time depends on the required conditions of the roads that are going to be repaired, interdependence, and resources availability. However, the findings indicated that increases beyond resource availability have no effect on the total completion time. Better results can be achieved in total completion time if arrival and completion times of available resources are properly synchronized. This research is a contribution on the importance of relations of precedence in the scheduling for road repair, the interdependence of resources and the special conditions of allocation between crews and type of machinery according to the affected track, and its impact on the completion times of the repair.application/pdfRojas Trejos, Carlos Alberto., Meisel, Jose D., Adarme-Jaimes, Wilson. y Orejuela Cabrera, Juan Pablo. (2025). Repair resources scheduling for attention of transitory road disruptions in humanitarian aid networks. Computers and Industrial Engineering, 203. DOI: 10.1016/j.cie.2025.11102010.1016/j.cie.2025.11102003608352https://hdl.handle.net/20.500.12313/6063https://www.sciencedirect.com/science/article/pii/S0360835225001664engElsevier LtdReino Unido203Computers and Industrial EngineeringAksu, D. T., & Ozdamar, L. (2014). A mathematical model for post-disaster road restoration: Enabling accessibility and evacuation. Transportation Research Part ELogistics and Transportation Review, 61, 56–67. https://doi.org/10.1016/j. tre.2013.10.009Alinaghian, M., Aghaie, M., & Sabbagh, M. S. (2019). A mathematical model for location of temporary relief centers and dynamic routing of aerial rescue vehicles. Computers and Industrial Engineering, 131(17), 227–241. https://doi.org/10.1016/j. cie.2019.03.002Arif, A., Wang, Z., Chen, C., & Chen, B. (2020). A stochastic multi-commodity logistic model for disaster preparation in distribution systems. IEEE Transactions on Smart Grid, 11(1), 565–576. https://doi.org/10.1109/TSG.2019.2925620Baxter, A. E., Wilborn Lagerman, H. E., & Keskinocak, P. (2020). Quantitative modeling in disaster management: A literature review. Retrieved from IBM Journal of Research and Development. https://www.scopus.com/inward/record.uri?eid=2-s2.0-850 81615488&doi=10.1147%2FJRD.2019.2960356&partnerID=40&md5=719517a 68324f26165a4852b4737e7c1Çelik, M. (2016). Network restoration and recovery in humanitarian operations: Framework, literature review, and research directions. Surveys in Operations Research and Management Science, 21(2), 47–61. https://doi.org/10.1016/j. sorms.2016.12.001Coco, A. A., Duhamel, C., & Santos, A. C. (2020). Modeling and solving the multi-period disruptions scheduling problem on urban networks. Annals of Operations Research, 285(1–2), 427–443. https://doi.org/10.1007/s10479-019-03248-5Edrissi, A., Nourinejad, M., & Roorda, M. J. (2015). Transportation network reliability in emergency response. Transportation Research Part E: Logistics and Transportation Review, 80, 56–73. https://doi.org/10.1016/j.tre.2015.05.005Habib, M. S., Lee, Y. H., & Memon, M. S. (2016). Mathematical models in humanitarian supply chain management: A systematic literature review. Mathematical Problems in Engineering, 2016. https://doi.org/10.1155/2016/3212095Iloglu, S, & Albert, L. A. (2020). A maximal multiple coverage and network restoration problem for disaster recovery. Operations Research Perspectives. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85076843383&doi=10.1016%2Fj. orp.2019.100132&partnerID=40&md5=9e783fa41570f20ac3be34a824402d8bIloglu, S., & Albert, L. A. (2018). An integrated network design and scheduling problem for network recovery and emergency response. Operations Research Perspectives, 5 (August), 218–231. https://doi.org/10.1016/j.orp.2018.08.001Kim, S., Shin, Y., Lee, G. M., & Moon, I. (2018). Network repair crew scheduling for short-term disasters. Applied Mathematical Modelling, 64, 510. https://doi.org/10.101 6/j.apm.2018.07.047Ibarra-Rojas, O. J., Hernandez, L., & Ozuna, L. (2018). The accessibility vehicle routing problem. Journal of Cleaner Production, 172, 1514–1528. https://doi.org/10.1016/j. jclepro.2017.10.249Li, C., Fang, Q., Ding, L., Cho, Y. K., & Chen, K. (2020). Time-dependent resilience analysis of a road network in an extreme environment. Transportation Research Part D: Transport and Environment, 85. https://doi.org/10.1016/j.trd.2020.102395Li, P., Lan, H., & Saldanha-Da-Gama, F. (2019). A Bi-objective capacitated locationrouting problem for multiple perishable commodities. IEEE Access, 7, 136729–136742. https://doi.org/10.1109/ACCESS.2019.2941363Lu, G., Xiong, Y., Ding, C., & Wang, Y. (2016). An optimal schedule for urban road network repair based on the greedy algorithm. PLoS ONE, 11(10). https://doi.org/ 10.1371/journal.pone.0164780Morshedlou, N., Barker, K., Nicholson, C. D., & Sansavini, G. (2018). Adaptive capacity planning formulation for infrastructure networks. Journal of Infrastructure Systems, 24(4). https://doi.org/10.1061/(ASCE)IS.1943-555X.0000432Nurre, S. G., Cavdaroglu, B., Mitchell, J. E., Sharkey, T. C., & Wallace, W. A. (2012). Restoring infrastructure systems: An integrated network design and scheduling (INDS) problem. European Journal of Operational Research, 223(3), 794–806. https:// doi.org/10.1016/j.ejor.2012.07.010Reddy, G. H., Chakrapani, P., Goswami, A. K., & Choudhury, N. B. D. (2017). Fuzzy based approach for restoration of distribution system during post natural disasters. IEEE Access, 6, 3448–3458. https://doi.org/10.1109/ACCESS.2017.2779823Rodriguez-Espindola, O., Albores, P., & Brewster, C. (2018). Dynamic formulation for humanitarian response operations incorporating multiple organisations. International Journal of Production Economics, 204(August), 83–98. https://doi.org/10.1016/j. ijpe.2018.07.023Sakuraba, C S, Santos, A. C., Prins, C., Bouillot, L., Durand, A., & Allenbach, B. (2016). Road network emergency accessibility planning after a major earthquake. EURO Journal on Computational Optimization. Retrieved from https://www.scopus.com/ inward/record.uri?eid=2-s2.0-85027971781&doi=10.1007%2Fs13675-016-0070- 2&partnerID=40&md5=656f79f6c423468df965487bccfed969.Sanci, E., & Daskin, M. S. (2019). Integrating location and network restoration decisions in relief networks under uncertainty. European Journal of Operational Research, 279 (2), 335–350. https://doi.org/10.1016/j.ejor.2019.06.012Shin, Y., Kim, S., & Moon, I. (2019). Integrated optimal scheduling of repair crew and relief vehicle after disaster. Computers and Operations Research, 105, 237–247. https://doi.org/10.1016/j.cor.2019.01.015Vahdani, B., Veysmoradi, D., Shekari, N., & Mousavi, S. M. (2018). Multi-objective, multi-period location-routing model to distribute relief after earthquake by considering emergency roadway repair. Neural Computing and Applications, 30(3), 835–854. https://doi.org/10.1007/s00521-016-2696-7Wu, J., & Wang, P. (2020). Post-disruption performance recovery to enhance resilience of interconnected network systems. Sustainable and Resilient Infrastructure. Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 85082017188&doi=10.1080%2F23789689.2019.1710073&partnerID=40 &md5=f4f461a1712f196f169974339afe5cf9.Yan, J., Hu, B., Xie, K., Tai, H. M., & Li, W. (2020). Post-disaster power system restoration planning considering sequence dependent repairing period. International Journal of Electrical Power and Energy Systems, 117. https://doi.org/10.1016/j. ijepes.2019.105612Yan, S., & Shih, Y.-L. (2009). Optimal scheduling of emergency roadway repair and subsequent relief distribution. Computers and Operations Research, 36(6), 2049–2065. https://doi.org/10.1016/j.cor.2008.07.002Zhang, Z., Wang, Z., & Zhou, H. (2020). An emergency resource allocation method based on supernetwork for urban disaster. Advances in Intelligent Systems and Computing, 1017, 248–255. https://doi.org/10.1007/978-3-030-25128-4_33Zhou, Y., Liu, J., Zhang, Y., & Gan, X. (2017). A multi-objective evolutionary algorithm for multi-period dynamic emergency resource scheduling problems. Transportation Research Part E: Logistics and Transportation Review, 99, 77–95. https://doi. org/10.1016/j.tre.2016.12.011.© 2025 The Author(s)info:eu-repo/semantics/closedAccesshttp://purl.org/coar/access_right/c_14cbAtribución 4.0 Internacional (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/Interrupciones viales transitorias - Redes de ayuda humanitariaAccess restorationHumanitarian logisticsMathematical modelRepair schedulingRepair resources scheduling for attention of transitory road disruptions in humanitarian aid networksArtículo de revistahttp://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Textinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionPublicationLICENSElicense.txtlicense.txttext/plain; charset=utf-8134https://repositorio.unibague.edu.co/bitstreams/aae2ab48-d4fb-47b3-b302-1cd2236931eb/download2fa3e590786b9c0f3ceba1b9656b7ac3MD51ORIGINALArtículo.pdfArtículo.pdfapplication/pdf256180https://repositorio.unibague.edu.co/bitstreams/761f0ad2-9d2c-44d6-a909-09b680e3a02e/downloadac467939f37bff194aa41369c19feb96MD51TEXTArtículo.pdf.txtArtículo.pdf.txtExtracted texttext/plain4733https://repositorio.unibague.edu.co/bitstreams/8075409e-4a45-44d7-83ed-e833ed2ec86d/download381a3457b9a0f1525fddcdff276e4b2dMD52THUMBNAILArtículo.pdf.jpgArtículo.pdf.jpgIM Thumbnailimage/jpeg28540https://repositorio.unibague.edu.co/bitstreams/3a6ccb8e-7b38-44a4-ad93-90dea5c61711/download80206dacbf62d712367577b14eb0758dMD5320.500.12313/6063oai:repositorio.unibague.edu.co:20.500.12313/60632025-11-29 03:02:30.953https://creativecommons.org/licenses/by/4.0/© 2025 The Author(s)https://repositorio.unibague.edu.coRepositorio Institucional Universidad de Ibaguébdigital@metabiblioteca.comQ3JlYXRpdmUgQ29tbW9ucyBBdHRyaWJ1dGlvbi1Ob25Db21tZXJjaWFsLU5vRGVyaXZhdGl2ZXMgNC4wIEludGVybmF0aW9uYWwgTGljZW5zZQ0KaHR0cHM6Ly9jcmVhdGl2ZWNvbW1vbnMub3JnL2xpY2Vuc2VzL2J5LW5jLW5kLzQuMC8= |