Superposition of Choice Functions and Its Application to Tornado Prediction and Search Problems

Fuad Aleskerov, Sergey Demin*, Sergey Shvydun

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

The paper examines the choice problem when the total number of observations and criteria is too large. There are many different procedures, which are used for decision-making process under multiple criteria; however, most of them cannot be applied to large datasets due to their computational complexity while others provide sufficient accuracy. To solve the problem, we consider the idea of superposition, which consists in the sequential application of choice functions where the result of the previous function is the input for the next function. Among the main benefits of the superposition are its manageable computational complexity and high performance. We analyze normative properties of the superposition that characterize how stable and sensible the final choice is. We also consider the application of superposition to tornado prediction and search problems. As a result, we show that superposition of choice functions provides higher efficiency values compared to traditional solutions.

Original languageEnglish
Article number68
JournalSN Computer Science
Volume1
Issue number2
DOIs
Publication statusPublished - Mar 2020
Externally publishedYes

Keywords

  • Composition
  • Normative properties
  • Search problem
  • Superposition
  • Tornado prediction

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