科研之友
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摘要
Group decision-making is an everyday evaluation activity in which a panel of decision-makers offers their preferences for obtaining the final results to solve decision problems. In the evaluation process, negotiation is essential for consensus reaching, usually realized by constructing an optimization-based consensus model in terms of a single optimization criterion, such as the amount of adjustment, the number of experts, and the cost of adjustment. Therefore, developing a comprehensive and practical consensus optimization model is crucial to achieving consensus efficiency and exploring a more desirable optimal result. This study concentrates on designing a two-stage consensus optimization model combining minimum adjustment and minimum cost under Pythagorean fuzzy linguistic preference information for realizing the consensus of the group decision-making problems in a complex and uncertain environment. In addition, the granulation of linguistic terms is carried out to reflect the uncertainty of decision-making information and promote consensus reaching within the optimal adaptability ranges of experts' opinions. The designed model satisfies the need for minimum costs for the mediator and considers experts' adjustment amount to shorten the time consumption, retain initial preference, and maximize the balance between the minimum amount of adjustment and the minimum cost. Finally, a case of evaluating container ships is presented to demonstrate the designed consensus model's practicality and effectiveness for risk evaluation by conducting comparative analyses.
