Abstract
How to select the optimal strategy to compete with rivals is one of the hottest issues in the multi-attribute decision-making (MADM) field. However, most of MADM methods not only neglect the characteristics of competitors’ behaviors but also just obtain a simple strategy ranking result cannot reflect the feasibility of each strategy. To overcome these drawbacks, a two-person non-cooperative matrix game method based on a hybrid dynamic expert weight determination model is proposed for coping with intricate competitive strategy group decision-making problems within q-rung orthopair fuzzy environment. At the beginning, a novel dynamic expert weight calculation model, considering objective individual and subjective evaluation information simultaneously, is devised by integrating the superiorities of a credibility analysis scale and a Hausdorff distance measure for q-rung orthopair fuzzy sets (q-ROFSs). The expert weights obtained by the above model can vary with subjective evaluation information provided by experts, which are closer to the actual practices. Subsequently, a two-person non-cooperative fuzzy matrix game is formulated to determine the optimal mixed strategies for competitors, which can present the specific feasibility and divergence degree of each competitive strategy and be less impacted by the number of strategies. Finally, an illustrative example, several comparative analyses and sensitivity analyses are conducted to validate the reasonability and effectiveness of the proposed approach. The experimental results demonstrate that the proposed approach as a CSGDM method with high efficiency, low computation complexity and little calculation burden.
Highlights
Two-person non-cooperative competitions exist universally in real-world practices
On account of the foregoing analyses, this paper aims at proposing a novel two-person fuzzy matrix game method for tackling competitive strategy group decision making (CSGDM) problems accurately and efficiently
A two-person non-cooperative fuzzy matrix game based on the variable weight theory and q-rung orthopair fuzzy sets (q-ROFSs) is proposed to deal with competitive strategy group decisionmaking problems
Summary
Two-person non-cooperative competitions exist universally in real-world practices. The selection of the optimal competitive strategy is vital for players to survive from current intensified competitive circumstances. A two-person non-cooperative fuzzy matrix game based on the variable weight theory and q-ROFSs is proposed to deal with competitive strategy group decisionmaking problems. The comparative results show that the proposed model is a powerful tool to assign reasonable weight to experts, which can portray experts’ objective individual information and vary with subjective evaluation information. In addition to the weighted average method integrated into the proposed approach, ideal point method and sequential optimization method, widely applied in market share competition strategy selection problems, are classical methods to solve fuzzy matrix models. (iii) The proposed two-person non-cooperative fuzzy matrix game decision-making method is less affected by the number of competitive strategies, and can pre-
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