НЕПАРАМЕТРИЧНІ МОДЕЛІ ТА ЗАСОБИ МОДЕЛЮВАННЯ НА ОСНОВІ ШІІНСТРУМЕНТАРІЮ В ЗАДАЧАХ УПРАВЛІННЯ ПРОЄКТАМИ.
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| Title: | НЕПАРАМЕТРИЧНІ МОДЕЛІ ТА ЗАСОБИ МОДЕЛЮВАННЯ НА ОСНОВІ ШІІНСТРУМЕНТАРІЮ В ЗАДАЧАХ УПРАВЛІННЯ ПРОЄКТАМИ. |
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| Alternate Title: | NON-PARAMETRIC MODELS AND SIMULATION TOOLS BASED ON AI TOOLKIT IN PROJECT MANAGEMENT PROBLEMS. |
| Authors: | Положаєнко, С. A.1 sanp277@gmail.com1, Кирпичов, Д. О.1 dmitry.kirp@gmail.com2 |
| Source: | Informatics & Mathematical Methods in Simulation / Informatika ta Matematičnì Metodi v Modelûvannì. 2026, Vol. 16 Issue 3, p534-540. 7p. |
| Subjects: | Project management, Resource management, Computer simulation, Team building, Nonparametric statistics, Software development tools, Mathematical optimization, Simulation software |
| Abstract: | Project resource management includes the processes necessary to identify, acquire, and manage the resources needed to successfully complete a project. These processes are designed to ensure that the necessary resources are provided to the project manager and his team at the right time and place. Project resource management includes, in particular (in a broad sense), such components as: resource management planning - that is, how to assess, acquire, manage, and use the project's material and human resources; operation resource assessment - is the assessment of the team's resources, the type and quantity of material, equipment, and consumables needed to complete the project; resource acquisition - or the involvement of team members, facilities, equipment, materials, consumables, and other resources needed to complete the project; team development, which involves improving the competencies, interactions between team members, and the general working conditions of the team to improve project performance; team management - otherwise - tracking the activities of team members, providing feedback, resolving problems, and managing changes in the team in order to optimize project performance; Resource control, which is related to ensuring that the material resources assigned and allocated to the project are available according to plan, as well as monitoring to compare planned and actual resource use and take necessary corrective actions. The above-mentioned list determines the diversity, non-algorithmic nature and uniqueness of the tasks related to project management. Moreover, in most cases, the solution of such tasks is complicated by significant amounts of information that need to be processed. In this context, artificial intelligence (AI) is considered not only as a tool for automating routine processes, but also as a powerful factor in optimizing management decisions at all stages of the life cycle of projects of various purposes (nature). In this sense, modeling becomes relevant in solving the specified tasks, the methodological basis of which is models, including non-parametric ones, which allow reflecting the structure of the studied process, and not only its quantitative (parametric) characteristics. At the same time, the advantage of modeling in project management tasks is also the fact that it is not the project itself that is studied - in its physical implementation, but a model (i.e. idealization) of the latter, which is important, in particular, at the planning stages. The effectiveness of modeling (for a selected range of tasks) is ensured by the use of AI tools capable of performing both complex calculations and intelligent data processing. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
| Abstract: | Project resource management includes the processes necessary to identify, acquire, and manage the resources needed to successfully complete a project. These processes are designed to ensure that the necessary resources are provided to the project manager and his team at the right time and place. Project resource management includes, in particular (in a broad sense), such components as: resource management planning - that is, how to assess, acquire, manage, and use the project's material and human resources; operation resource assessment - is the assessment of the team's resources, the type and quantity of material, equipment, and consumables needed to complete the project; resource acquisition - or the involvement of team members, facilities, equipment, materials, consumables, and other resources needed to complete the project; team development, which involves improving the competencies, interactions between team members, and the general working conditions of the team to improve project performance; team management - otherwise - tracking the activities of team members, providing feedback, resolving problems, and managing changes in the team in order to optimize project performance; Resource control, which is related to ensuring that the material resources assigned and allocated to the project are available according to plan, as well as monitoring to compare planned and actual resource use and take necessary corrective actions. The above-mentioned list determines the diversity, non-algorithmic nature and uniqueness of the tasks related to project management. Moreover, in most cases, the solution of such tasks is complicated by significant amounts of information that need to be processed. In this context, artificial intelligence (AI) is considered not only as a tool for automating routine processes, but also as a powerful factor in optimizing management decisions at all stages of the life cycle of projects of various purposes (nature). In this sense, modeling becomes relevant in solving the specified tasks, the methodological basis of which is models, including non-parametric ones, which allow reflecting the structure of the studied process, and not only its quantitative (parametric) characteristics. At the same time, the advantage of modeling in project management tasks is also the fact that it is not the project itself that is studied - in its physical implementation, but a model (i.e. idealization) of the latter, which is important, in particular, at the planning stages. The effectiveness of modeling (for a selected range of tasks) is ensured by the use of AI tools capable of performing both complex calculations and intelligent data processing. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 22235744 |
| DOI: | 10.15276/imms.v16.no3.534 |
