Multi-Attribute evaluation-based graph model for conflict resolution considering heterogeneous behaviors

Abstract

The graph model for conflict resolution (GMCR) is a useful tool for modeling and analyzing conflicts. In a conflict, the decision maker (DM)’s evaluation of feasible states is often influenced by multiple attributes. When in different feasible states, DMs may assign different importance to each attribute. Therefore, this paper applies multi-attribute evaluation (MAE) to GMCR and proposes the MAE-based stability definition. In addition, due to differences in relationships and opinions among DMs, opponents will behave differently in response to the action of the focal DM. To analyze the heterogeneous behavior of opponents, this paper proposes a heterogeneous behavior analysis method based on social network analysis (SNA) and opinion similarity. Then, the MAE-based mixed stability definitions are proposed to perform the stability analysis considering heterogeneous behaviors. Finally, this paper applies the proposed method to the Elmira contamination conflict and makes a sensitivity analysis to prove the validity of the proposed method.