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A multi-attribute quantum group consensus model considering psychological
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AI
DOI：10.1016/j.engappai.2025.110086.png)
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Abstract
En 中文
In response to the issues of information uncertainty and opinion interference in meteorological disaster emergency rescue, this paper proposes a multi-attribute quantum group decision-making model. Firstly, the paper employs the linguistic Z-numbers to represent the evaluation information of decision-makers in complex uncertain decision-making environments. Secondly, a group consensus model based on minimal adjustments is constructed, considering the psychological state and adjustment willingness of decision-makers when facing group preference pressure. On this basis, the weights of decision-makers are determined by incorporating their marginal contribution levels. Meanwhile, an optimization model is developed based on the marginal contributions from Shapley to determine the optimal attributes' weights. Furthermore, a quantum-like Bayesian network is constructed to compute the quantum probabilities of alternatives and rank them, while utilizing Deng entropy measure to address the interference terms in the quantum probabilities. Finally, through the analysis of simulation data, the applicability of the model in evaluating emergency alternatives for meteorological disasters is verified, and its stability and practicality are further demonstrated through sensitivity analysis, comparative analysis and simulation analysis. The result shows that combining quantum computing with artificial intelligence achieves efficient consensus in intelligent group decision-making processes.
Keywords:
Multi-attribute quantum group decision making
Group consensus
Quantum computing
Artificial intelligence
Deng entropy
Linguistic Z-numbers
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