Graph model for conflict resolution for mixed-stability combinatorial foresight based on the combination of regret theory and VIKOR method

The graph model for conflict resolution (GMCR) is a branch of decision-making; therefore, how to scientifically abstract the evaluative thinking of decision-makers (DMs) has always been a core research point in decision science. In this context, further consideration of the heterogeneous behavior of competitors and their impact on the evolution of conflicts deserves special attention. Usually, DMs' evaluation thinking has certain ambiguity and uncertainty, and they are accustomed to giving qualitative evaluation information. Given the unique advantages of trapezoidal interval type-2 fuzzy sets (TrIT2FS) in the fusion of decision domains and transformational linguistic expressions, this paper constructs a theoretical framework for a graph model on TrIT2FS and proposes a method for calculating DMs preference ranking and a heterogeneous combinatorial foresight stability function. Firstly, the DMs will consider multiple factors in the decision evaluation process, and there are specific regret avoidance psychological behavior characteristics; thus, this paper integrates VIKOR and regret theory to solve the DM's preference ranking and expands on a new preference ranking method. Secondly, mixed stability definitions based on TrIT2FS are proposed to facilitate the description of different sanctioning behaviors of heterogeneous opponents. Subsequently, a heterogeneous combinatorial foresight stability function is proposed to quickly obtain conflict evolution solutions in complex dynamic conflict problems based on the extended mixed stability definitions. Finally, to thoroughly test the correctness and practicality of the proposed theory, the conflict between inputs and outputs of the technological transformation of enterprises under the low-carbon strategy is used as a specific application scenario and example for validation.