Optimizing an integrated home care problem: a heuristic-based decision-support system
With the continuous increase in longevity worldwide, the elderly population requiring home health and social care has been continuously growing over the years. Planning combined home health and social services has been shown to be a very difficult task for current decision-makers, not only due to th...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya) |
| Repositorio: | Recercat. Dipósit de la Recerca de Catalunya |
| OAI Identifier: | oai:recercat.cat:10230/58649 |
| Acceso en línea: | http://hdl.handle.net/10230/58649 http://dx.doi.org/10.1016/j.engappai.2022.105062 |
| Access Level: | acceso abierto |
| Palabra clave: | Operations research Home social care Home health care Greedy heuristics Multi-criteria decision making Scheduling and routing |
| Sumario: | With the continuous increase in longevity worldwide, the elderly population requiring home health and social care has been continuously growing over the years. Planning combined home health and social services has been shown to be a very difficult task for current decision-makers, not only due to the high number of working regulations and user-related necessities that need to be considered but also due to the need for synchronizing both types of services. Moreover, it is highly desirable that users are visited by the fewest number of different caregivers in the same kind of appointments (continuity of service). The complex and multi-objective nature of the synchronized home health and social care routing and scheduling problem has called for the development of automated planning systems that are able to obtain efficient solutions in reasonable computational times. In this work, we propose two heuristic methods to optimize routing and scheduling decisions for this problem with an extensive set of constraints and objectives. We use (real) data and information from current care providers in the Barcelona area to build and test our models and provide insights into parameter tuning and the trade-off between the associated operating costs, continuity of service and number of unscheduled services. The proposed tool is made available via a web-based decision support system that allows decision-makers to obtain efficient solutions in an intuitive, complete, and timely manner. |
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