Modeling Business Processes of IT Projects Using Queueing Theory
The article is devoted to the modeling of business processes of IT projects using queueing theory, where business processes are interpreted as service systems with random task flows and limited resources. The relevance of the research is determined by the growing complexity of IT projects, where ran...
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| Datum: | 2025 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | Ukrainisch |
| Veröffentlicht: |
Кам'янець-Подільський національний університет імені Івана Огієнка
2025
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| Online Zugang: | http://mcm-math.kpnu.edu.ua/article/view/338521 |
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| Назва журналу: | Mathematical and computer modelling. Series: Physical and mathematical sciences |
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Mathematical and computer modelling. Series: Physical and mathematical sciences| Zusammenfassung: | The article is devoted to the modeling of business processes of IT projects using queueing theory, where business processes are interpreted as service systems with random task flows and limited resources. The relevance of the research is determined by the growing complexity of IT projects, where random task arrivals, changing requirements, and variability in execution time lead to queues, resource overuse, and deadline violations. In today’s competitive environment and the need for rapid product delivery to the market, the application of queueing theory becomes an instrument for scientifically grounded management, enabling minimization of delays, improvement of productivity, and ensuring system stability. The aim of the study is to develop a mathematical framework based on service system theory for modeling business processes of IT projects, which will optimize resource allocation, determine the optimal number of performers, and minimize delays in task execution. The research applies analytical methods of queueing theory for calculating key indicators such as utilization factor, average number of tasks in the system, waiting time, and probability of losses. Additionally, simulation modeling was carried out using software tools such as Arena to reproduce the dynamics of processes with variable service time distributions. The obtained scientific results demonstrate that modeling IT project business processes with queueing theory ensures system stability under conditions when resource utilization does not exceed the critical level. The optimal number of performers is determined through the assessment of waiting probability, which contributes to the reduction of delays in queues and the overall task execution cycle. Analytical models, such as single-channel and multi-channel systems, have shown the effectiveness of workload distribution among teams, especially under conditions of limited queue length, where the risk of task loss decreases. Prospects for further research include the integration of queueing theory with machine learning methods for adaptive modeling of real IT projects, taking into account priority queues and multi-agent systems |
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