ArticleExpert systems with applications2023
A sustainable and efficient home health care network design model under uncertainty.
Article in Expert systems with applications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Exploring a career pathway for home support workers in Ireland: a systematic scoping review of the international evidence.Frontiers in health services · 2024Article
- Robust design of a logistics system using FePIA procedure and analysis of trade-offs between COHeliyon · 2023Article
- Home Health Care Problem with Synchronization Visits and Considering Samples Transferring Time: A Case Study in Tehran, Iran.International journal of environmental research and public health · 2022Article
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Authors and funding
4 authors.
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Abstract
To cater to the increasing demands, particularly during diseases such as Covid-19, the design and planning of home health care systems is of significant importance. The current study proposes a multi-objective mixed-integer linear model for a home health care network in two stages; the first is the opening of efficient health centres, and the second is the routing and scheduling considering corporate social responsibility and efficiency. There are multiple objectives that we consider, including minimization of total costs and inefficiency considerations, and maximization of social aspects. A novel aspect of this study is the consideration of social responsibility, which includes employment opportunities and regional economic development, and efficiency in terms of time, energy, and mismanagement of budgets. To measure efficiency, an augmented version of the data envelopment analysis approach is incorporated into the proposed optimization model. Additionally, the TH approach is developed as an interactive fuzzy method to deal with the proposed multi-objective model. Within the HHC problem, costs, social factors, and service time are inherently uncertain, and hence, to solve this problem, a robust-fuzzy approach is proposed. The ensuing model is applied to a real case study of Kermanshah in Iran. Moreover, several problem instances motivated by real cases are generated with different characteristics to measure the performance of the proposed model and approach. The results show that decision-makers' preferences play a key role in human resource planning and regional development. Furthermore, the results confirm the efficiency of the proposed approach in different instances within reasonable time frames.
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