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Foresight of the federal district's innovation system evolution using a multiobjective genetic algorithm

Vol. 26, Iss. 6, JUNE 2020

Received: 14 May 2020

Received in revised form: 28 May 2020

Accepted: 11 June 2020

Available online: 29 June 2020

Subject Heading: Financial system

JEL Classification: C63, E17, O21, O36

Pages: 1208–1227

https://doi.org/10.24891/fc.26.6.1208

Yashin S.N. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
jashinsn@yandex.ru

https://orcid.org/0000-0002-7182-2808

Koshelev E.V. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation
ekoshelev@yandex.ru

https://orcid.org/0000-0001-5290-7913

Sukhanov D.A. Non-State Educational Private Institution for Further Professional Education BIOTA–PLUS, Nizhny Novgorod, Russian Federation
svx85@yandex.ru

https://orcid.org/0000-0002-4600-0108

Subject. This article deals with the issues related to the introduction of simulation technologies in business processes based on the data bulk processing.
Objectives. The article intends to propose the use of simulation modeling in public administration, namely at the level of interregional cooperation in certain federal districts.
Methods. For the study, we used a proposed model of foresight of the federal district's innovation system evolution, based on the use of a multiobjective genetic algorithm.
Results. The article offers specific ways, approaches and solutions to enhance the synergies of the federal district.

Keywords: foresight, intercluster interaction, simulation, multiobjective genetic algorithm

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