PROBLEMS OF ІNFORMATION AND ANALYTICAL SUPPORT OF FUNCTIONING AND DEVELOPMENT OF ENTERPRISES OF PRINTING INDUSTRY IN THE CONDITIONS OF COMPETITION
DOI:
https://doi.org/10.24025/2306-4412.2.2020.197895Keywords:
artificial life, optimization of functioning, multiagent system, decision making, models of efficiency indicators, methods of data recovery.Abstract
Small and medium-sized enterprises are a potential driver of Ukraine's modern economy. The large part of the market is occupied by the enterprises of printing industry. Their managers constantly come across the tasks of expanding production, re-profiling, upgrading, setting up branches or eliminating them. Given the dynamic nature of the operation of such enterprises and its duality of the process of multiagent systems functioning, it is proposed to solve such a problem on the basis of evolutionary and multiagent paradigms. As the enterprises of the industry evolve over time, it is shown that in their modeling the ideas of the concept of "artificial life" can be used, their peculiarities, advantages and disadvantages are established. The analytical review of models, methods and software-algorithmic tools, used in the processes of support of manufacturing enterprises by stages of their life cycle, is carried out. The analysis shows the benefits of using multiagent systems in decision support systems in homogeneous environments. Models have been built to modify multiple tasks or production structures or management strategies based on predefined rules. The features of building an intelligent decision support system and experimental verification of results are presented. The functional structure of modular interaction in the decision support system is proposed. Features of modules functioning are defined, their input and output data flows, features of functioning and critical modes are specified. The peculiarities of forming a knowledge base, including a database of transactions, a bank of mathematical models, a variety of mathematical methods and rules for obtaining new knowledge, are shown. The analysis of the recommendations contained in the knowledge base significantly increases the chances of the manager to make informed progressive decisions. The above results are, in aggregate, the solution to scientific and applied research problem.References
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Copyright (c) 2020 Богдан Вікторович Мисник, Руслан Борисович Капітан, Людмида Дмитрівна Мисник, Олександр Васильович Манзюра The authors who publish in this journal agree to the following terms:The authors reserve the right to authorship of their work and give the journal the right to first publish this work under the terms of the Creative Commons Attribution License CC BY-NC, which allows other persons to freely distribute published work with a mandatory reference to authors of the original work and the first publication of the work in this journal.
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