1. Mitigating supply chain disruptions in plywood manufacturing by deadline reorderingOlivér Ősz, József Garab, Máté Hegyháti, Balázs Dávid, 2026, original scientific article Abstract: Disruptions in supply networks have caused many logistical and planning challenges in the last few years. The previous predictability of the shipping times of raw materials changed drastically due to various global issues, which affected many production areas, including the wood industry. This work is motivated by a case study of a Central European plywood production facility, where supply-side disruptions caused difficulties in meeting deadlines for downstream companies of the construction and furniture industry. As a result, the objective of production planners shifted towards mitigating the financial burden caused by cancellation penalties. Three MILP (Mixed-Integer Linear Programming) models and a genetic algorithm were developed to tackle the scheduling of a plywood production plant with raw material shipments and order deadlines. The novelty of the considered problem lies in the flexibility of swapping order deadlines from the same client, which was inspired by the real-life deals of the aforementioned company. The methods were tested on 120 benchmark instances of different sizes generated from real industrial data. The genetic algorithm terminated within 60 s for all instances and found the optimal or best-known solution in 71 of 80 short-horizon instances, while also remaining efficient on larger 30-day cases. As the solution approach is not specific to plywood production, it can be applied to scheduling problems in other fields as well, where similar disruptions can develop, and the production process features are covered by the Multi-Mode Resource-Constrained Project Scheduling Problem class.
Keywords: plywood, scheduling, MRCPSP, MILP, genetic algorithm
Published in RUP: 01.06.2026; Views: 223; Downloads: 6
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3. 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: 1532; Downloads: 3
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4. 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: 1832; Downloads: 7
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7. Extending BIM for air quality monitoringMichael Nicolas Mrissa, Jan Vcelak, László Hajdu, Balázs Dávid, Miklós Ferenz Krész, Jakub Michal Sandak, Anna Malgorzata Sandak, Rok Kanduti, Monika Varkonji, Anja Jutraž, Katja Malovrh Rebec, 2020, published scientific conference contribution Keywords: Building Information Model, internet of things, environmental quality monitoring, healthy living
Published in RUP: 06.05.2021; Views: 3216; Downloads: 122
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9. Integrating service life simulations of building facades with BIM to reduce economic and environmental impactsJakub Michal Sandak, Anna Malgorzata Sandak, Miklós Ferenz Krész, Balázs Dávid, László Hajdu, Michael Nicolas Mrissa, Črtomir Tavzes, Anja Jutraž, Boris Deanovič, Katja Malovrh Rebec, 2020, published scientific conference contribution abstract Keywords: service life modelling, aesthetical limit state, biomaterials for building facades, visualization of aesthetical deterioration
Published in RUP: 07.12.2020; Views: 3267; Downloads: 19
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