Abstract
Internal hospital logistics (IHL) involves the scheduling of materials and patient transportations employing a fleet of transporters. The problem of collecting and delivering these items within a hospital can be modeled as a Pickup and Delivery Problem with Time Windows (PDPTW). This paper proposes a hybrid dynamic optimization to address the IHL problem based on a two-step heuristic. This algorithm combines reactive and periodic optimizations to assign logistic’s transports to the most suitable transporters while considering the urgency of each transport. To conserve resources, this algorithm addresses logistics transports with higher urgency reactively and handles less urgent transports periodically. The initial assignment is constructed using the earliest due date first (EDDF) assignment method. To further improve the efficiency of the procedure, a ruin and recreate heuristic is developed and tested. Computational experiments have been conducted utilizing hospital data from a large hospital with approximately 2100 beds located in Germany to evaluate the performance of the proposed dynamic hybrid optimization. Results show that the hybrid policy outperforms the baseline reactive policy used in the hospital in terms of service quality and cost efficiency.
This research was conducted at the Fraunhofer Institute for Material Flow and Logistics as part of the KIK-Dispo project, funded by the Federal Ministry of Education and Research of Germany (Grant No. 01IS19041B). The responsibility for the content lies with the authors.
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The OECD (Organisation for Economic Co-operation and Development) is an international organization made up of 38 member countries. These member countries are generally considered to be developed, industrialized economies with relatively high levels of economic growth, stability, and well-being.
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Ehsanfar, E., Karami, F., Kerkenhoff, T. (2023). A Reactive-Periodic Hybrid Optimization for Internal Hospital Logistics. In: Daduna, J.R., Liedtke, G., Shi, X., Voß, S. (eds) Computational Logistics. ICCL 2023. Lecture Notes in Computer Science, vol 14239. Springer, Cham. https://doi.org/10.1007/978-3-031-43612-3_3
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