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Chernyshev Y.O., Ventsov N.N., Pshenichnyi I.S. —
A possible method of allocating resources in destructive conditions
// Cybernetics and programming.
– 2018. – ¹ 5.
– P. 1 - 7.
DOI: 10.25136/2306-4196.2018.5.27626 URL: https://en. nbpublish.com/library_read_article.php?id=27626
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The subject of research is the approach to the allocation of resources in terms of possible destructive conditions.The object of the research is a model of decision-making processes of a distributional nature under the conditions of possible destructive influences. The authors consider the issues of modeling the processes of resource flow distribution under the conditions of possible undesirable effects. It is shown that the use of relative fuzzy estimates of resource transfer routes is more expedient than modeling the entire resource allocation area in terms of the time complexity of the decision-making process, since, based on statistical and expert assessments, route preferences can be quickly determined from the point of view of guaranteed resource transfer under destructive impacts.
The research method is based on the use of set theory, fuzzy logic, evolutionary and immune approaches. The use of fuzzy preference relations reduces the time to build a model, and the use of evolutionary and immune methods to speed up the search for a solution. The main conclusion of the study is the possibility of using relative fuzzy estimates of the preferences of the used routes when organizing the allocation of resources. An algorithm for the allocation of resources in the context of destructive influences is proposed, a distinctive feature of which is the use of information about previously implemented resource allocations in the formation of a set of initial solutions. Verification of the solutions obtained is supposed to be carried out using the method of negative selection - one of the methods of modeling the immune system. Modification of existing solutions is advisable to produce, for example, using the methods of evolutionary modeling.
decision making, modeling, adaptation, intellectual method, optimization, distribution, fuzziness, evolution, immune approach, flows
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