This article is cited in 2 papers

Application of decision support methods for the multicriterial selection of multiscale compositions

K. K. Abgaryan^ab, V. A. Osipova<sup>b

a</sup> Dorodnicyn Computing Center, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44/2 Vavilov Str., Moscow, 119333, Russian Federation
^b Moscow Aviation Institute (National Research University), 4 Volokolamskoe Shosse, Moscow 125080, Russian Federation

Abstract: The article discusses the use of decision-making support methods for the task of selecting multiscale compositions (MC) — computational analogues of multiscale physical and mathematical models created for analyzing *various heterogeneous processes associated with the formation of new composite materials with predetermined properties. When solving specific problems, different multiscale models and their corresponding MC can be constructed. The question arises of comparing these models and assessing their “effectiveness” for specific problem. On the stage of predictive modeling, the authors propose a methodology for comparison of multiscale models through evaluation and selection of appropriate MC using methods of decision-making support under multiple criteria. As an illustration of the possibility of choosing the best alternative in the presence of additional information on evaluation criteria of MC, a model example associated with the study of electronic and structural properties of thin films InN (GaN) on silicon substrates is considered.

Keywords: multiscale modeling, decision theory, quality criteria, alternative, decision support methods, multiple criteria, value function.

Received: 15.11.2018

DOI: 10.14357/19922264190207

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