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Modelling the spread of infectious diseases in public transport systems under varying demand patterns and capacity constraints
László Hajdu, Jovan Pavlović, Miklós Ferenz Krész, András Bóta, 2025, izvirni znanstveni članek

Opis: Understanding the dynamics of passenger interactions and their epidemiological impact across public transportation systems is crucial for both service efficiency and public health. High passenger density and close physical proximity have been shown to accelerate the spread of infectious diseases. During the COVID-19 pandemic, many public transportation companies took measures to slow down and minimize the spread of the disease. One of these measures was introducing spacing and capacity constraints on public transit vehicles. Our objective is to explore the effects of changes in demand and transportation measures from an epidemiological point of view, offering alternative measures to public transportation companies to keep the system operational while minimizing the epidemiological risk as much as possible. Our findings show that restricting vehicle capacity can significantly reduce the spread of infections, while demand-related measures have an even stronger effect. Combining these approaches offers the best solutions for balancing public health and operability.
Ključne besede: agent based modelling, infectious diseases, network analysis
Objavljeno v RUP: 27.08.2025; Ogledov: 498; Prenosov: 3
.pdf Celotno besedilo (3,94 MB)
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An assignment model for scheduling vehicles with refueling
Viktor Árgilán, János Balogh, Jozsef Bekesi, Balázs Dávid, Gábor Galambos, Miklós Ferenz Krész, Attila Tóth, 2025, izvirni znanstveni članek

Opis: 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.
Ključne besede: vehicle scheduling, vehicle assignment, refueling constraints, fuel types, IP based solution
Objavljeno v RUP: 25.07.2025; Ogledov: 879; Prenosov: 2
.pdf Celotno besedilo (427,48 KB)

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Scheduling truck arrivals for efficient container flow management in port logistics
Daniil Baldouski, Miklós Ferenz Krész, Balázs Dávid, 2025, izvirni znanstveni članek

Opis: 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.
Ključne besede: scheduling, port logistics, container flow optimization, simulation, mixed-integer linear programming
Objavljeno v RUP: 04.07.2025; Ogledov: 901; Prenosov: 5
.pdf Celotno besedilo (1,98 MB)
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MATCOS-13 : proceedings of the 2013 mini-conference on applied theoretical computer science
2016, zbornik recenziranih znanstvenih prispevkov na mednarodni ali tuji konferenci

Ključne besede: elektronske knjige, zborniki
Objavljeno v RUP: 07.11.2021; Ogledov: 3055; Prenosov: 19
.pdf Celotno besedilo (3,31 MB)

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