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Maximal Generalized Network Flow Accounting for Motivation Cover

Maximal Generalized Network Flow Accounting for Motivation

Open Access
|Jun 2024

Abstract

In the present work, the maximal generalized network flow, often referred to as the profit-loss flow, is examined, considering the motivation in the decision-making systems built on this flow. The general description of the features of motivation as a psychological process actively involved in decision-making systems through the generalized network flow is given. A method is proposed to embed motivation in a generalized network flow through the motivation coefficients on different network sections (arcs). It is shown that the proposed method offers more possibilities than the classical network flow. It is proven that the initial resource in the source does not match the final resource in the consumer. This has been suggested to be due to the influence of motivation. The theoretical and experimental results convincingly prove the possibilities of considering motivation in decision-making systems when managing the transportation of resources in an arbitrary transport network.

DOI: https://doi.org/10.2478/cait-2024-0012 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 3 - 15
Submitted on: Apr 12, 2024
Accepted on: May 30, 2024
Published on: Jun 27, 2024
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2024 Vassil Sgurev, Lyubka Doukovska, Ekaterina Tsopanova, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.