Multi-resources co-scheduling optimization for home healthcare services under the constraints of service time windows and green transportation

Resource sharing among different communities and medical centers is an effective method to solve the inefficiency of healthcare resource use and unequal distribution of medical resources across regions. This study aims at optimizing the resource arrangement in home health care services by multi-reso...

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Vydáno v:Applied soft computing Ročník 131; s. 109746
Hlavní autoři: Du, Gang, Tian, Yao, Ouyang, Xiaoling
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.12.2022
Témata:
Co-scheduling
Home healthcare
Multi-regions Tabu Search algorithm
Multi-resources
Multi-regions Tabu Search algorithm
Co-scheduling
Multi-resources
Home healthcare
ISSN:1568-4946, 1872-9681
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Shrnutí:Resource sharing among different communities and medical centers is an effective method to solve the inefficiency of healthcare resource use and unequal distribution of medical resources across regions. This study aims at optimizing the resource arrangement in home health care services by multi-resources co-scheduling. Specifically, we consider several important constraints including cross-distinct income in the constructed model. A Multi-Regions Tabu Search Algorithm is proposed to realize co-scheduling of multi-medical-staff in different communities to improve the calculation speed and obtain a better solution. We take the PuTuo district in Shanghai as an example for empirical analysis to verify the effectiveness of the proposed model and algorithm. Sensitivity analysis is then conducted by changing the service capabilities of communities. Results indicate that the total cost can be effectively reduced by multi-resources co-scheduling under different service capacities. However, the levels of cost reduction are distinct in different situations. •We optimize resource arrangement in home healthcare service by multi-resources co-scheduling.•We propose a Multi-Regions-Tabu Search Algorithm to realize co-scheduling.•The empirical analysis verified the effectiveness of the proposed model and algorithm.•The total cost can be effectively reduced by multi-resources co-scheduling.
ISSN:1568-4946
1872-9681
DOI:10.1016/j.asoc.2022.109746