Krstev, Aleksandar and Krstev, Dejan and Dimitrov, Sasko (2021) Data Processing Using Analytical Hierarchical Process in Real Circumstances. In: ITRO 2021, 26 Nov 2021, Zrenjanin, Republic of Serbia.
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Abstract
In the development of the industry of small and medium enterprises that are involved in one of the most specific activities such as working with products, materials it gives and seeks opportunities for optimizing the basic management activities in the work of a company. Today, many data are constantly generated that require proper processing and access to them, especially when it comes to supply chain management and business logistics. Standard processing techniques may not meet these requirements. The development of information technology and decision theory has contributed to the emergence of the application of modern-applicable methods and approaches to data processing and analysis. The way of processing data from traditional data processing tools are adapted for data processing and with the help of tools and mathematical methods that enable processing and analysis of big data that depend on several criteria such as time, resources, quality, and distance when it is about delivering work material. The identification and analysis of the problem to be solved, the determination of the possible solutions to the problem, the criteria according to which the possible solutions are evaluated, i.e., the alternatives and the choice of the best possible solution is a decision-making process. It is the choice of the best, from the most possible alternative solutions to the problem such as the problem of delivery of specific material such as leather considering the quality and price.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | Natural sciences > Computer and information sciences Natural sciences > Matematics Natural sciences > Other natural sciences |
| Divisions: | Faculty of Computer Science |
| Depositing User: | Aleksandar Krstev |
| Date Deposited: | 08 Nov 2022 11:31 |
| Last Modified: | 08 Nov 2022 11:31 |
| URI: | https://eprints.ugd.edu.mk/id/eprint/30457 |
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