Features of Network Flow Systems for Decision Making with Motivation Accounting

Abstract

The present work investigates the problem of considering the influence of motivation in discrete network flow decision-making systems. Motivation is the primary factor that drives people to achieve their goals and plays a key role in decision-making systems. A method is proposed by which this influence is accounted for using the arc flow function amplification or attenuation coefficients. These operations are in the class of generalized network flows (flows with gains and losses). Methods to determine both the maximal and minimal value of the generalized network flow with consideration of the motivation are proposed A numerical example of a decision-making system based on a generalized network flow with motivation accounting is described, which confirms the obtained theoretical results.