1. Outcomes of digital nursing schedules : a systematic literature reviewAnton Grmšek Svetlin, Melita Peršolja, 2025, review article Abstract: The purpose of this literature review was to identify the evidence on the outcomes of digitalisation of schedules in nursing. Data were gathered from CINAHL, Medline, Cochrane Library, PubMed, ScienceDirect, JSTOR and SpringerLink electronic databases. Seventy-four relevant literature items were identified. Ten studies published between 2015 and 2024 were evaluated and critically analysed using the JBI Critical Appraisal Checklist: four systematic literature reviews, three quasi-experimental studies, two case studies, and one qualitative descriptive study. The literature on electronic schedules in nursing reports on a variety of positive and negative impacts on nurses, patients and healthcare organisations. The introduction of electronic schedules in nursing is has mainly positive consequences, because if appropriately implemented, it leads to better patient health outcomes and increased job satisfaction among nurses. However, the developments in the field are ongoing and more research on that topic is needed before a firmer conclusion can be reached.
Keywords: digitalisation, nursing, roster, staffing and scheduling
Published in RUP: 24.08.2025; Views: 468; Downloads: 7
 Full text (375,49 KB) |
2. An assignment model for scheduling vehicles with refuelingViktor Árgilán, János Balogh, Jozsef Bekesi, Balázs Dávid, Gábor Galambos, Miklós Ferenz Krész, Attila Tóth, 2025, original scientific article Abstract: The vehicle scheduling problem consists of scheduling a fleet of vehicles to cover a set of tasks at a minimum cost. The tasks are given in predetermined time intervals, and the vehicles are supplied by different depots. There are several known mathematical models that can be used to solve this problem, resulting in a valid vehicle schedule. One such approach is the multi-commodity network flow model, where the optimal schedule is computed by solving a linear integer programming problem. The main disadvantage of this model is that it can be intractable for practical scenarios that include additional vehicle constraints. These are specific restrictions that come from real-world applications, such as the refueling requirement of vehicles. When vehicles of different fuel types, including environmentally friendly ones, are considered, decisions about their refueling include many additional constraints that a valid assignment must meet. This paper presents how these vehicle-specific tasks can be included in the vehicle assignment phase. An IP-based heuristic solution is given for this specific variant of the vehicle assignment with multiple depots. Computational results on real-life and randomly generated test instances are presented where the vehicle assignment model uses an input schedule generated by the time-space network approach. The resulting integer programming problem for this assignment can be solved extremely quickly, even with a large number of variables. Computational results demonstrate that the model can effectively extend the capabilities of the standard models to be able to handle the assignment with vehicle-specific task requirements.
Keywords: vehicle scheduling, vehicle assignment, refueling constraints, fuel types, IP based solution
Published in RUP: 25.07.2025; Views: 934; Downloads: 2
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3. Scheduling truck arrivals for efficient container flow management in port logisticsDaniil Baldouski, Miklós Ferenz Krész, Balázs Dávid, 2025, original scientific article Abstract: The management of truck arrivals at container terminals is crucial for efficient port operations. Congestions developing both outside and inside the gates can cause logistical problems, while also having a significant impact on the environment and the surroundings of the port. Therefore, optimizing truck queues outside the gates of the port, as well as routing of trucks inside the terminals can lead to an improve- ment in the overall efficiency of the port processes. This paper presents a mixed- integer linear programming formulation to determine these optimal truck routes and schedules. The model considers a port with an external parking lot, multiple gates, internal roadways, and docks. A rolling horizon heuristic is also developed for the solution of instances where the model is otherwise intractable. The developed meth- ods are evaluated on instances simulated based on real-world data.
Keywords: scheduling, port logistics, container flow optimization, simulation, mixed-integer linear programming
Published in RUP: 04.07.2025; Views: 996; Downloads: 5
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