Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks
Pandemics and sudden disease outbreaks place considerable stress on hospital resources. Their increasing numbers in recent years has necessitated investment in disaster risk management strategies, particularly in the healthcare sector. The sudden surge of patients, particularly in requesting ambulan...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | Progress in Disaster Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590061723000157 |
| _version_ | 1797802144483508224 |
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| author | Maziar Yazdani Milad Haghani |
| author_facet | Maziar Yazdani Milad Haghani |
| author_sort | Maziar Yazdani |
| collection | DOAJ |
| description | Pandemics and sudden disease outbreaks place considerable stress on hospital resources. Their increasing numbers in recent years has necessitated investment in disaster risk management strategies, particularly in the healthcare sector. The sudden surge of patients, particularly in requesting ambulance services, overwhelms hospital systems and compromises health service delivery. Failure of health planners to respond immediately to a sudden disease outbreak can result in insufficient distribution of healthcare services and can thereby exacerbate the death toll dramatically. The current research aims to develop an optimisation-based integrated decision model to assist healthcare decision-makers with immediate and effective planning for ambulances to move critical patients from their residences to hospitals, considering the available capacities of each hospital. Several lemmas for the problem are proposed, and based on these; several local search methods are developed to improve the performance of the proposed optimisation method. To confirm the efficacy of the proposed approach, a comprehensive comparison is conducted. In conclusion, sensitivity analyses are performed to discuss some practical insights. The proposed models can be adopted to develop decision tools that enable hospital system managers to optimize their resources to changing healthcare needs in disease outbreaks. |
| first_indexed | 2024-03-13T05:01:16Z |
| format | Article |
| id | doaj.art-edcc12399e5e489e9e73aa5c2a87963d |
| institution | Directory Open Access Journal |
| issn | 2590-0617 |
| language | English |
| last_indexed | 2024-03-13T05:01:16Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Progress in Disaster Science |
| spelling | doaj.art-edcc12399e5e489e9e73aa5c2a87963d2023-06-17T05:20:28ZengElsevierProgress in Disaster Science2590-06172023-04-0118100288Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaksMaziar Yazdani0Milad Haghani1Corresponding author.; Research Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, The University of New South Wales, UNSW, Sydney, AustraliaResearch Centre for Integrated Transport Innovation (rCITI), School of Civil and Environmental Engineering, The University of New South Wales, UNSW, Sydney, AustraliaPandemics and sudden disease outbreaks place considerable stress on hospital resources. Their increasing numbers in recent years has necessitated investment in disaster risk management strategies, particularly in the healthcare sector. The sudden surge of patients, particularly in requesting ambulance services, overwhelms hospital systems and compromises health service delivery. Failure of health planners to respond immediately to a sudden disease outbreak can result in insufficient distribution of healthcare services and can thereby exacerbate the death toll dramatically. The current research aims to develop an optimisation-based integrated decision model to assist healthcare decision-makers with immediate and effective planning for ambulances to move critical patients from their residences to hospitals, considering the available capacities of each hospital. Several lemmas for the problem are proposed, and based on these; several local search methods are developed to improve the performance of the proposed optimisation method. To confirm the efficacy of the proposed approach, a comprehensive comparison is conducted. In conclusion, sensitivity analyses are performed to discuss some practical insights. The proposed models can be adopted to develop decision tools that enable hospital system managers to optimize their resources to changing healthcare needs in disease outbreaks.http://www.sciencedirect.com/science/article/pii/S2590061723000157COVID-19Genetic algorithmDisasterTransportationOptimisation approach |
| spellingShingle | Maziar Yazdani Milad Haghani Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks Progress in Disaster Science COVID-19 Genetic algorithm Disaster Transportation Optimisation approach |
| title | Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks |
| title_full | Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks |
| title_fullStr | Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks |
| title_full_unstemmed | Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks |
| title_short | Optimisation-based integrated decision model for ambulance routing in response to pandemic outbreaks |
| title_sort | optimisation based integrated decision model for ambulance routing in response to pandemic outbreaks |
| topic | COVID-19 Genetic algorithm Disaster Transportation Optimisation approach |
| url | http://www.sciencedirect.com/science/article/pii/S2590061723000157 |
| work_keys_str_mv | AT maziaryazdani optimisationbasedintegrateddecisionmodelforambulanceroutinginresponsetopandemicoutbreaks AT miladhaghani optimisationbasedintegrateddecisionmodelforambulanceroutinginresponsetopandemicoutbreaks |