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

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