A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm
Objective: This study assesses a multi-period capacitated maximal-covering location-allocation model for healthcare services, taking interservice referral as well as equity access into account.Methods: A two-stage optimization strategy is used to formulate the model. In the first stage, facilities a...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-02-01
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| Series: | International Journal of Public Health |
| Subjects: | |
| Online Access: | https://www.ssph-journal.org/articles/10.3389/ijph.2023.1605015/full |
| _version_ | 1797893768158904320 |
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| author | Azadeh Salami Behrouz Afshar-Nadjafi Maghsoud Amiri |
| author_facet | Azadeh Salami Behrouz Afshar-Nadjafi Maghsoud Amiri |
| author_sort | Azadeh Salami |
| collection | DOAJ |
| description | Objective: This study assesses a multi-period capacitated maximal-covering location-allocation model for healthcare services, taking interservice referral as well as equity access into account.Methods: A two-stage optimization strategy is used to formulate the model. In the first stage, facilities are located to maximize covered demand, and in the second stage, patients are allocated to capacitated facilities based on their radius of coverage over multiple time periods. The problem, which belongs to the NP-hard class of optimization problems, is solved using a linear mixed-integer programming (MILP) model.Results: A numerical example is presented to evaluate the efficiency of the proposed model. In addition, to identify near-optimal solutions for large instances, a hybrid genetic-sequential quadratic programming approach (GA-SQP) is developed. To examine the performance and efficiency of the GA-SQP, we employed several randomly generated test instances of various sizes and compared them to those obtained using the exact method.Conclusion: The proposed model has demonstrated an excellent ability in locating healthcare facilities and allocating health services while taking shortage and equity into account during each time period. |
| first_indexed | 2024-04-10T06:58:55Z |
| format | Article |
| id | doaj.art-42d85e44cb5d46838e2cf39f4e1f4974 |
| institution | Directory Open Access Journal |
| issn | 1661-8564 |
| language | English |
| last_indexed | 2024-04-10T06:58:55Z |
| publishDate | 2023-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | International Journal of Public Health |
| spelling | doaj.art-42d85e44cb5d46838e2cf39f4e1f49742023-02-28T04:11:03ZengFrontiers Media S.A.International Journal of Public Health1661-85642023-02-016810.3389/ijph.2023.16050151605015A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic AlgorithmAzadeh Salami0Behrouz Afshar-Nadjafi1Maghsoud Amiri2Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranDepartment of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, IranDepartment of Industrial Management, Faculty of Management and Accounting, Allameh Tabataba’i University, Tehran, IranObjective: This study assesses a multi-period capacitated maximal-covering location-allocation model for healthcare services, taking interservice referral as well as equity access into account.Methods: A two-stage optimization strategy is used to formulate the model. In the first stage, facilities are located to maximize covered demand, and in the second stage, patients are allocated to capacitated facilities based on their radius of coverage over multiple time periods. The problem, which belongs to the NP-hard class of optimization problems, is solved using a linear mixed-integer programming (MILP) model.Results: A numerical example is presented to evaluate the efficiency of the proposed model. In addition, to identify near-optimal solutions for large instances, a hybrid genetic-sequential quadratic programming approach (GA-SQP) is developed. To examine the performance and efficiency of the GA-SQP, we employed several randomly generated test instances of various sizes and compared them to those obtained using the exact method.Conclusion: The proposed model has demonstrated an excellent ability in locating healthcare facilities and allocating health services while taking shortage and equity into account during each time period.https://www.ssph-journal.org/articles/10.3389/ijph.2023.1605015/fullhealthcarehierarchical facility location-allocationhealth service network designmulti-periodhybrid genetic algorithm |
| spellingShingle | Azadeh Salami Behrouz Afshar-Nadjafi Maghsoud Amiri A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm International Journal of Public Health healthcare hierarchical facility location-allocation health service network design multi-period hybrid genetic algorithm |
| title | A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm |
| title_full | A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm |
| title_fullStr | A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm |
| title_full_unstemmed | A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm |
| title_short | A Two-Stage Optimization Approach for Healthcare Facility Location- Allocation Problems With Service Delivering Based on Genetic Algorithm |
| title_sort | two stage optimization approach for healthcare facility location allocation problems with service delivering based on genetic algorithm |
| topic | healthcare hierarchical facility location-allocation health service network design multi-period hybrid genetic algorithm |
| url | https://www.ssph-journal.org/articles/10.3389/ijph.2023.1605015/full |
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