A novel methodology for multi-agent decision-making based on N-soft sets

Abstract

AbstractMulti-criteria decision analysis with multiple agents provides tools for the research and development of intelligent applications. The solution strategy depends largely on the structure of the data. In this paper we propose a decide-then-merge approach to the problem of multi-agent multi-criteria decision-making when each individual data comes in the form of an N-soft set. To this purpose, we present a methodology that works in two steps. First, with each individual input we associate a ranking. This can be done in several ways, since individual decisions based on N-soft sets are well developed. Then with the help of voting theory, we merge all these rankings and produce a final ranking of the alternatives. The steps of this method are explained with synthetic examples. We argue that the proposed strategy is highly adaptable because both stages of our scheme can be customized by the user. A real case study in the framework of Operational Research illustrates the application of this method in detail. Finally, we perform a comparative analysis with existing methodologies.