Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution

This paper conducts a comparative analysis of advanced methodologies aimed at addressing the intricate task of scheduling medical supplies in both civilian and military sectors for epidemic prevention and control. This study introduces a multi-objective water wave optimization (MOWWO) algorithm and...

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Autores:: Guerrero, Bethsy
Quintero M., Christian G.
Viloria-Núñez, César
Jimeno Paba, Miguel Ángel

Tipo de recurso:: Article of journal

Fecha de publicación:: 2024

Institución:: Universidad Tecnológica de Bolívar

Repositorio:: Repositorio Institucional UTB

Idioma:: eng

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network_acronym_str	UTB2
network_name_str	Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
dc.title.translated.spa.fl_str_mv	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
title	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
spellingShingle	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution Artificial intelligence MOWWO DAMOWWO Emergency Management
title_short	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
title_full	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
title_fullStr	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
title_full_unstemmed	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
title_sort	Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution
dc.creator.fl_str_mv	Guerrero, Bethsy Quintero M., Christian G. Viloria-Núñez, César Jimeno Paba, Miguel Ángel
dc.contributor.author.eng.fl_str_mv	Guerrero, Bethsy Quintero M., Christian G. Viloria-Núñez, César Jimeno Paba, Miguel Ángel
dc.subject.eng.fl_str_mv	Artificial intelligence MOWWO DAMOWWO Emergency Management
topic	Artificial intelligence MOWWO DAMOWWO Emergency Management
description	This paper conducts a comparative analysis of advanced methodologies aimed at addressing the intricate task of scheduling medical supplies in both civilian and military sectors for epidemic prevention and control. This study introduces a multi-objective water wave optimization (MOWWO) algorithm and enhance its efficacy by incorporating a dynamically adjusted component to the metaheuristic approach (DAMOWWO). The primary goal of this research is to assess the proposed approach in contrast to established state of the art methods with similar objectives. The aim of this study is to optimize multiple aspects simultaneously, including the overall satisfaction rates of medical supply delivery and the reduction of scheduling costs, while ensuring a minimum military supply reservation ratio. This paper offers a comprehensive evaluation of the MOOW algorithm, emphasizing its potential applications in emergency response scenarios.
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-12-24 00:00:00
dc.date.available.none.fl_str_mv	2024-12-24 00:00:00
dc.date.issued.none.fl_str_mv	2024-12-24
dc.type.spa.fl_str_mv	Artículo de revista
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dc.type.local.eng.fl_str_mv	Journal article
dc.type.content.eng.fl_str_mv	Text
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dc.identifier.url.none.fl_str_mv	https://doi.org/10.32397/tesea.vol5.n2.620
dc.identifier.doi.none.fl_str_mv	10.32397/tesea.vol5.n2.620
dc.identifier.eissn.none.fl_str_mv	2745-0120
url	https://doi.org/10.32397/tesea.vol5.n2.620
identifier_str_mv	10.32397/tesea.vol5.n2.620 2745-0120
dc.language.iso.eng.fl_str_mv	eng
language	eng
dc.relation.references.eng.fl_str_mv	Arismendy, L., Cárdenas, C., Gómez, D., Maturana, A., Mejía, R., & Quintero M, C. G. (2021). A prescriptive intelligent system for an industrial wastewater treatment process: analyzing Ph as a first approach. Sustainability, 13(8), 4311.J. [2] Pérez, W., Tello, A., Saquicela, V., Vidal, M. E., & La Cruz, A. (2015, August). An automatic method for the enrichment of dicom metadata using biomedical ontologies. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2551-2554). IEEE. [3] J. Torres, N. Perez, A. Pinto, M. Macea, S. Castaño, and E. Delgado, "Novel Lee Model for Prediction of Propagation Path Loss in Digital Terrestrial Television Systems in Montevideo City, Uruguay," Advances in Intelligent Systems and Computing, No 1066, pp. 542- 553, 2020. [4] S. Khezr, M. Moniruzzaman, A. Yassine, and R. Benlamri, "Blockchain technology in healthcare: A comprehensive review and directions for future research," Applied Sciences, vol. 9, no. 9, p. 1736, 2019. [5] I. Syahrir, S. Suparno, and I. Vanany, "Healthcare and Disaster Supply Chain: Literature Review and Future Research," Faculty of Technic, Muhammadiyah University of Surabaya, Surabaya 60113, Indonesia, Department of Industrial Engineering, Sepuluh Nopember Institute of Technology, Surabaya 60111, Indonesia, Available online 23 December 2015, Version of Record 23 December 2015. [6] G. Richey Jr, "The supply chain crisis and disaster pyramid: A theoretical framework for understanding preparedness and recovery," International Journal of Physical Distribution & Logistics Management, vol. 39, no. 7, pp. 619-628, 2009. [7] A. Parody, M. Castillo, S. Galvis, P. S. Mendoza, and V. Santiago, "HDI and Air Quality: from Multivariate Statistics and Machine Learning," in 2023 IEEE Colombian Caribbean Conference (C3), Nov. 2023, pp. 1-6. [8] C. P. Bown, "How COVID-19 medical supply shortages led to extraordinary trade and industrial policy," Asian Economic Policy Review, vol. 17, no. 1, pp. 114-135, 2022. [9] J. D. VanVactor, "Healthcare logistics in disaster planning and emergency management: A perspective," Journal of Business Continuity & Emergency Planning, vol. 10, no. 2, pp. 157-176, 2017. [10] Shao, Kaili, Ying Song, and Bo Wang. "PGA: a new hybrid PSO and GAmethodfortask scheduling with deadline constraints in distributed computing." Mathematics 11.6 (2023): 1548. [11] Shen, Ling, et al. "A hybrid GA-PSO algorithm for seru scheduling problem with dynamic resource allocation." International Journal of Manufacturing Research 18.1 (2023): 100-124. [12] H.-F. Ling, Z.-L. Su, X.-L. Jiang, and Y.-J. Zheng, “Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control,” Healthcare, vol. 9, no. 2, p. 126, Jan. 2021, doi: 10.3390/healthcare9020126. [13] F. Goodarzian, H. Hosseini-Nasab, and M. B. Fakhrzad, "A multi-objective sustainable medicine supply chain network design using a novel hybrid multi-objective metaheuristic algorithm," International Journal of Engineering, vol. 33, no. 10, pp. 1986-1995, 2020. [14] P. Ghasemi, K. Khalili-Damghani, A. Hafezalkotob, and S. Raissi, "Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake)," Socio-Economic Planning Sciences, vol. 71, p. 100745, 2020. [15] Q. Wang, Z. Liu, P. Jiang, y L. Luo, "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, vol. 82, p. 101279, 2022. [16] L.G. Hernández-Pérez and J.M. Ponce-Ortega, "Multi-objective Optimization Approach Based on Deterministic and Metaheuristic Techniques to Resource Management in Health Crisis Scenarios Under Uncertainty," Process Integration and Optimization for Sustainability, vol. 5, pp. 429-443, Jan. 13, 2021. DOI: 10.1007/s41660-020-00154-3 [17] F. Torabi Yeganeh and S.H. Zegordi, "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, vol. 285, pp. 161-196, Feb. 2020. DOI: 10.1007/s10479-019-03375-z [18] X. Wu, J. Liao, and Z. Wang, "Water Wave Optimization for the Traveling Salesman Problem," in Proceedings of the Lecture Notes in Computer Science, vol. 9225, 2015, pp. [19] H. Zhu, T. Jiang, Y. Wang, and G. Deng, "Multi-objective discrete water wave optimization algorithm for solving the energy-saving job shop scheduling problem with variable processing speeds," Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10617-10631, 2021. DOI: 10.3233/JIFS-201522. [20] Z. Y. Rong, M. X. Zhang, Y. C. Du, and Y. J. Zheng, "A Hybrid Evolutionary Algorithm for Combined Road-Rail Emergency Transportation Planning," in Lecture Notes in Computer Science, vol. 10941, 2018, pp. 1485. [21] Z. Shao, D. Pi, and W. Shao, "A novel multi-objective discrete water wave optimization for solving multi-objective blocking flow-shop scheduling problem," Knowledge-Based Systems, vol. 165, pp. 110-131, 2019. [22] Y. Lu, J. Lu and T. Jiang, "Energy-Conscious Scheduling Problem in a Flexible Job Shop Using a Discrete Water Wave Optimization Algorithm," in IEEE Access, vol. 7, pp. 101561-101574, 2019, doi: 10.1109/ACCESS.2019.2930281. [23] Y.-J. Zheng, X.-Q. Lu, Y.-C. Du, Y. Xue, and W.-G. Sheng, "Water wave optimization for combinatorial optimization: Design strategies and applications," Appl. Soft Comput., vol. 83, p. 105611, 2019. [24] B. Guerrero, M. Valle, M. Restrepo, J. A. Cardona, C. Viloria-Núñez and C. G. Quintero M., "Multi-Objective Particle Swarm Optimization Approach for Population Classification in Emergency Management," 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), Orlando, FL, USA, 2023, pp. 452-459, doi: 10.1109/SERA57763.2023.10197646. [25] B. G. Granados, C. G. Quintero M, C. Viloria-Núñez and M. Á. J. Paba, "Multi-Objective Optimization for Medical Supplies Storage and Distribution in Disaster Management," 2023 IEEE Colombian Caribbean Conference (C3), Barranquilla, Colombia, 2023, pp. 1-6. [26] Y. Guan, M. Lv, S. Li, Y. Su, and S. Dong, "Optimized sensor placement of water supply network based on multi-objective white whale optimization algorithm," Water, vol. 15, no. 15, p. 2677, 2023. [27] Y. J. Zheng, X. Q. Lu, Y. C. Du, Y. Xue, and W. G. Sheng, "Water wave optimization for combinatorial optimization: Design strategies and applications," Applied Soft Computing, vol. 83, p. 105611, 2019. [28] K. Jamuna and K. S. Swarup, "Multi-objective biogeography based optimization for optimal PMU placement," Appl. Soft Comput., vol. 12, no. 5, pp. 1503-1510, 2012.
dc.relation.ispartofjournal.eng.fl_str_mv	Transactions on Energy Systems and Engineering Applications
dc.relation.citationvolume.eng.fl_str_mv	5
dc.relation.citationstartpage.none.fl_str_mv	1
dc.relation.citationendpage.none.fl_str_mv	12
dc.relation.bitstream.none.fl_str_mv	https://revistas.utb.edu.co/tesea/article/download/620/423
dc.relation.citationedition.eng.fl_str_mv	Núm. 2 , Año 2024 : Transactions on Energy Systems and Engineering Applications
dc.relation.citationissue.eng.fl_str_mv	2
dc.rights.eng.fl_str_mv	Bethsy Guerrero, Christian G. Quintero M., César Viloria-Núñez, Miguel Ángel Jimeno Paba - 2024
dc.rights.uri.eng.fl_str_mv	https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.eng.fl_str_mv	info:eu-repo/semantics/openAccess
dc.rights.creativecommons.eng.fl_str_mv	This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.eng.fl_str_mv	http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv	Bethsy Guerrero, Christian G. Quintero M., César Viloria-Núñez, Miguel Ángel Jimeno Paba - 2024 https://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv	openAccess
dc.format.mimetype.eng.fl_str_mv	application/pdf
dc.publisher.eng.fl_str_mv	Universidad Tecnológica de Bolívar
dc.source.eng.fl_str_mv	https://revistas.utb.edu.co/tesea/article/view/620
institution	Universidad Tecnológica de Bolívar
repository.name.fl_str_mv	Repositorio Digital Universidad Tecnológica de Bolívar
repository.mail.fl_str_mv	bdigital@metabiblioteca.com
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spelling	Guerrero, BethsyQuintero M., Christian G.Viloria-Núñez, CésarJimeno Paba, Miguel Ángel2024-12-24 00:00:002024-12-24 00:00:002024-12-24This paper conducts a comparative analysis of advanced methodologies aimed at addressing the intricate task of scheduling medical supplies in both civilian and military sectors for epidemic prevention and control. This study introduces a multi-objective water wave optimization (MOWWO) algorithm and enhance its efficacy by incorporating a dynamically adjusted component to the metaheuristic approach (DAMOWWO). The primary goal of this research is to assess the proposed approach in contrast to established state of the art methods with similar objectives. The aim of this study is to optimize multiple aspects simultaneously, including the overall satisfaction rates of medical supply delivery and the reduction of scheduling costs, while ensuring a minimum military supply reservation ratio. This paper offers a comprehensive evaluation of the MOOW algorithm, emphasizing its potential applications in emergency response scenarios.application/pdfengUniversidad Tecnológica de BolívarBethsy Guerrero, Christian G. Quintero M., César Viloria-Núñez, Miguel Ángel Jimeno Paba - 2024https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.utb.edu.co/tesea/article/view/620Artificial intelligenceMOWWODAMOWWOEmergency ManagementEnhancing disaster management through multi-objective water wave optimization for medical supplies storage and distributionEnhancing disaster management through multi-objective water wave optimization for medical supplies storage and distributionArtículo de revistainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Journal articleTextinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85https://doi.org/10.32397/tesea.vol5.n2.62010.32397/tesea.vol5.n2.6202745-0120Arismendy, L., Cárdenas, C., Gómez, D., Maturana, A., Mejía, R., & Quintero M, C. G. (2021). A prescriptive intelligent system for an industrial wastewater treatment process: analyzing Ph as a first approach. Sustainability, 13(8), 4311.J. [2] Pérez, W., Tello, A., Saquicela, V., Vidal, M. E., & La Cruz, A. (2015, August). An automatic method for the enrichment of dicom metadata using biomedical ontologies. In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 2551-2554). IEEE. [3] J. Torres, N. Perez, A. Pinto, M. Macea, S. Castaño, and E. Delgado, "Novel Lee Model for Prediction of Propagation Path Loss in Digital Terrestrial Television Systems in Montevideo City, Uruguay," Advances in Intelligent Systems and Computing, No 1066, pp. 542- 553, 2020. [4] S. Khezr, M. Moniruzzaman, A. Yassine, and R. Benlamri, "Blockchain technology in healthcare: A comprehensive review and directions for future research," Applied Sciences, vol. 9, no. 9, p. 1736, 2019. [5] I. Syahrir, S. Suparno, and I. Vanany, "Healthcare and Disaster Supply Chain: Literature Review and Future Research," Faculty of Technic, Muhammadiyah University of Surabaya, Surabaya 60113, Indonesia, Department of Industrial Engineering, Sepuluh Nopember Institute of Technology, Surabaya 60111, Indonesia, Available online 23 December 2015, Version of Record 23 December 2015. [6] G. Richey Jr, "The supply chain crisis and disaster pyramid: A theoretical framework for understanding preparedness and recovery," International Journal of Physical Distribution & Logistics Management, vol. 39, no. 7, pp. 619-628, 2009. [7] A. Parody, M. Castillo, S. Galvis, P. S. Mendoza, and V. Santiago, "HDI and Air Quality: from Multivariate Statistics and Machine Learning," in 2023 IEEE Colombian Caribbean Conference (C3), Nov. 2023, pp. 1-6. [8] C. P. Bown, "How COVID-19 medical supply shortages led to extraordinary trade and industrial policy," Asian Economic Policy Review, vol. 17, no. 1, pp. 114-135, 2022. [9] J. D. VanVactor, "Healthcare logistics in disaster planning and emergency management: A perspective," Journal of Business Continuity & Emergency Planning, vol. 10, no. 2, pp. 157-176, 2017. [10] Shao, Kaili, Ying Song, and Bo Wang. "PGA: a new hybrid PSO and GAmethodfortask scheduling with deadline constraints in distributed computing." Mathematics 11.6 (2023): 1548. [11] Shen, Ling, et al. "A hybrid GA-PSO algorithm for seru scheduling problem with dynamic resource allocation." International Journal of Manufacturing Research 18.1 (2023): 100-124. [12] H.-F. Ling, Z.-L. Su, X.-L. Jiang, and Y.-J. Zheng, “Multi-Objective Optimization of Integrated Civilian-Military Scheduling of Medical Supplies for Epidemic Prevention and Control,” Healthcare, vol. 9, no. 2, p. 126, Jan. 2021, doi: 10.3390/healthcare9020126. [13] F. Goodarzian, H. Hosseini-Nasab, and M. B. Fakhrzad, "A multi-objective sustainable medicine supply chain network design using a novel hybrid multi-objective metaheuristic algorithm," International Journal of Engineering, vol. 33, no. 10, pp. 1986-1995, 2020. [14] P. Ghasemi, K. Khalili-Damghani, A. Hafezalkotob, and S. Raissi, "Stochastic optimization model for distribution and evacuation planning (A case study of Tehran earthquake)," Socio-Economic Planning Sciences, vol. 71, p. 100745, 2020. [15] Q. Wang, Z. Liu, P. Jiang, y L. Luo, "A stochastic programming model for emergency supplies pre-positioning, transshipment and procurement in a regional healthcare coalition," Socio-Economic Planning Sciences, vol. 82, p. 101279, 2022. [16] L.G. Hernández-Pérez and J.M. Ponce-Ortega, "Multi-objective Optimization Approach Based on Deterministic and Metaheuristic Techniques to Resource Management in Health Crisis Scenarios Under Uncertainty," Process Integration and Optimization for Sustainability, vol. 5, pp. 429-443, Jan. 13, 2021. DOI: 10.1007/s41660-020-00154-3 [17] F. Torabi Yeganeh and S.H. Zegordi, "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, vol. 285, pp. 161-196, Feb. 2020. DOI: 10.1007/s10479-019-03375-z [18] X. Wu, J. Liao, and Z. Wang, "Water Wave Optimization for the Traveling Salesman Problem," in Proceedings of the Lecture Notes in Computer Science, vol. 9225, 2015, pp. [19] H. Zhu, T. Jiang, Y. Wang, and G. Deng, "Multi-objective discrete water wave optimization algorithm for solving the energy-saving job shop scheduling problem with variable processing speeds," Journal of Intelligent & Fuzzy Systems, vol. 40, no. 6, pp. 10617-10631, 2021. DOI: 10.3233/JIFS-201522. [20] Z. Y. Rong, M. X. Zhang, Y. C. Du, and Y. J. Zheng, "A Hybrid Evolutionary Algorithm for Combined Road-Rail Emergency Transportation Planning," in Lecture Notes in Computer Science, vol. 10941, 2018, pp. 1485. [21] Z. Shao, D. Pi, and W. Shao, "A novel multi-objective discrete water wave optimization for solving multi-objective blocking flow-shop scheduling problem," Knowledge-Based Systems, vol. 165, pp. 110-131, 2019. [22] Y. Lu, J. Lu and T. Jiang, "Energy-Conscious Scheduling Problem in a Flexible Job Shop Using a Discrete Water Wave Optimization Algorithm," in IEEE Access, vol. 7, pp. 101561-101574, 2019, doi: 10.1109/ACCESS.2019.2930281. [23] Y.-J. Zheng, X.-Q. Lu, Y.-C. Du, Y. Xue, and W.-G. Sheng, "Water wave optimization for combinatorial optimization: Design strategies and applications," Appl. Soft Comput., vol. 83, p. 105611, 2019. [24] B. Guerrero, M. Valle, M. Restrepo, J. A. Cardona, C. Viloria-Núñez and C. G. Quintero M., "Multi-Objective Particle Swarm Optimization Approach for Population Classification in Emergency Management," 2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA), Orlando, FL, USA, 2023, pp. 452-459, doi: 10.1109/SERA57763.2023.10197646. [25] B. G. Granados, C. G. Quintero M, C. Viloria-Núñez and M. Á. J. Paba, "Multi-Objective Optimization for Medical Supplies Storage and Distribution in Disaster Management," 2023 IEEE Colombian Caribbean Conference (C3), Barranquilla, Colombia, 2023, pp. 1-6. [26] Y. Guan, M. Lv, S. Li, Y. Su, and S. Dong, "Optimized sensor placement of water supply network based on multi-objective white whale optimization algorithm," Water, vol. 15, no. 15, p. 2677, 2023. [27] Y. J. Zheng, X. Q. Lu, Y. C. Du, Y. Xue, and W. G. Sheng, "Water wave optimization for combinatorial optimization: Design strategies and applications," Applied Soft Computing, vol. 83, p. 105611, 2019. [28] K. Jamuna and K. S. Swarup, "Multi-objective biogeography based optimization for optimal PMU placement," Appl. Soft Comput., vol. 12, no. 5, pp. 1503-1510, 2012.Transactions on Energy Systems and Engineering Applications5112https://revistas.utb.edu.co/tesea/article/download/620/423Núm. 2 , Año 2024 : Transactions on Energy Systems and Engineering Applications220.500.12585/13546oai:repositorio.utb.edu.co:20.500.12585/135462025-09-16 09:15:14.776https://creativecommons.org/licenses/by/4.0Bethsy Guerrero, Christian G. Quintero M., César Viloria-Núñez, Miguel Ángel Jimeno Paba - 2024metadata.onlyhttps://repositorio.utb.edu.coRepositorio Digital Universidad Tecnológica de Bolívarbdigital@metabiblioteca.com

Enhancing disaster management through multi-objective water wave optimization for medical supplies storage and distribution

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