Статья 'Возможный способ распределения ресурсов в условиях деструктивных воздействий' - журнал 'Кибернетика и программирование' - NotaBene.ru
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Cybernetics and programming
Reference:

A possible method of allocating resources in destructive conditions

Chernyshev Yurii Olegovich

Doctor of Technical Science

Professor, Department of Automation of Production Processes, Don State Technical University

344000, Russia, Rostovskaya oblast', g. Rostov-na-Donu, ploshchad' Gagarina, 1

myvnn@list.ru
Другие публикации этого автора
 

 
Ventsov Nikolai Nikolaevich

PhD in Technical Science

Associate Professor, Department of Information Technology, Don State Technical University

344000, Russia, Rostovskaya oblast', g. Rostov-na-Donu, ploshchad' Gagarina, 1

vencov@list.ru
Другие публикации этого автора
 

 
Pshenichnyi Igor' Sergeevich

Adjunct, Krasnodar Higher Military School

350063, Russia, g. Krasnodar, ul. Krasina, 4

valleyigor@mail.ru

DOI:

10.25136/2306-4196.2018.5.27626

Review date:

09-10-2018


Publish date:

03-11-2018


Abstract.

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.

Keywords: decision making, modeling, adaptation, intellectual method, optimization, distribution, fuzziness, evolution, immune approach, flows
This article written in Russian. You can find full text of article in Russian here .

References
1.
Shell J, Coupland S. Fuzzy Transfer Learning: Methodology and Application// Preprint submitted to Information Sciences May 23, 2014.-27 p.
2.
Pankov S.E., Petrov V.F., Arkhipkin A.V., Gureev A.V. Planirovanie radiopokrytiya oblasti primeneniya RTK VN kak sposob uvelicheniya nadezhnosti i skrytnosti ego funktsionirovaniya Izvestiya YuFU. Tekhnicheskie nauki.-2018.-№ 1 (195).-S. 6-14.
3.
Lebedev B.K., Lebedev O.B., Lebedeva E.M. Raspredelenie resursov na osnove gibridnykh modelei roevogo intellekta // Nauchno-tekhnicheskii vestnik informatsionnykh tekhnologii, mekhaniki i optiki. 2017. T. 17. № 6. S. 1063–1073. doi: 10.17586/2226-1494-2017-17-6-1063-1073
4.
Zolotarev A.A. Metody optimizatsii raspredelitel'nykh protsessov. M.: Infra-Inzheneriya, 2014. 160 s.
5.
Brucker P. Scheduling Algorithms. 5th ed. Springer, 2007. 379 p.
6.
Bershtein L.S., Karelin V.P., Tselykh A.N. Metody i algoritmy prinyatiya reshenii pri chetkikh i nechetkikh iskhodnykh dannykh: Uchebnoe posobie. Taganrog: Izd-vo TRTU, 2000. 92 s.
7.
Seraya O.V. Raspredelitel'naya zadacha lineinogo programmirovaniya // Sistemy obrabotki informatsii. 2013. № 2 (109). S. 167–170.
8.
Bershtein L.S., Belyakov S.L., Bozhenyuk A.V. Marshrutizatsiya v usloviyakh neopredelennosti s ispol'zovaniem nechetkikh temporal'nykh vneshne ustoichivykh mnozhestv// Izvestiya YuFU. Tekhnicheskie nauki. – 2013. – № 1 – S. 82-89.
9.
Matveikin I.V., Popov I.V. Opredelenie osnovnykh parametrov integrirovannoi modeli obrabotki informatsii//IS-IT18: tr. Mezhdunar. kongr. po intellekt. sistemam i inform. tekhnologiyam, p. Divnomorskoe, 2-9 sent. / YuFU. – Tananrog, 2018, T.2, S.163-167.
10.
Pogonin V.A. Modeli dispetcherskogo upravleniya robotami// Informatsionnye protsessy i upravlenie. – 2006. – № 1, S 45–55.
11.
Zhukovin V. Nechetkie mnogokriterial'nye modeli prinyatiya reshenii. Tbilisi: "Metsniereba", 1988.-71 s.
12.
Dey A. Understanding and Using Context // Personal and ubiquitous computing. – 2001. – No. 5. – P. 4-7.
13.
Dourish P. What we talk about when we talk about context // Personal Ubiquitous Comput. – 2004. – No. 8. – P. 19-30.
14.
Bettini C., Brdiczka O., Henricksen K., Indulska J., Nicklas D., Ranganathan A., Riboni D. A survey of context modelling and reasoning techniques // Pervasive and Mobile Computing. – 2010. – No. 6. – P. 161-180.
15.
Geneticheskie algoritmy/ Pod red. V.M. Kureichika.– 2-e izd., ispr. i dop.-M.: FIZMATLIT, 2006. – 320 s.
16.
Agibalov O.I., Ventsov N.N. Otsenka zavisimostei vremeni raboty geneticheskogo algoritma, vypolnyaemogo na CPU i GPU // Kibernetika i programmirovanie. — 2017.-№ 6.-S.1-8. DOI: 10.25136/2306-4196.2017.6.24509. URL: http://e-notabene.ru/kp/article_24509.html
17.
Iskusstvennye immunnye sistemy i ikh primenenie /Pod red. D. Dasgupty. Per. s angl. pod red A.A. Romanyukhi. — M.: FIZMATLIT, 2006. — 344 s.-ISBN 5-9221-0706-2
18.
D. Dasgupta, S. Forrest. Novelty Detection in Time Series Data using Ideas from Immunology. Fifth International Conference on Intelligent Systems. Reno, Nevada: June, 1996
19.
Chernyshev Yu.O., Ventsov N.N. Razrabotka dekoderov iskusstvennoi immunnoi sistemy, vospriimchivykh k nechetkim komandam // Kibernetika i programmirovanie. — 2016.-№ 5.-S.213-221. DOI: 10.7256/2306-4196.2016.5.19885. URL: http://e-notabene.ru/kp/article_19885.html
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