This paper investigates the multiobjective supplier selection problem (SSP) with type-2 fuzzy parameters. All the involved parameters such as aggregate demand, budget allocation, quota flexibility, rating values, are depicted as type-2 triangular fuzzy (T-2TF) parameters. To tackle the T-2TF, first, critical values (CV)-based reduction method is introduced, and then chance-constrained programming is modeled to obtain the crisp version of the multiobjective SSP. Secondly, an interval-based approximation method is also developed for defuzzifying the T-2TF parameters. Further, a novel interactive neutrosophic programming approach is also suggested to solve the deterministic multiobjective SSP, which allows the decision-makers to incorporate the neutral thoughts or indeterminacy degrees efficiently. The computational study is presented to verify and validate the defuzzfied techniques and the proposed solution approach. An ample opportunity to select the most desired compromise solution with maximum overall satisfaction level is also addressed. Finally, the conclusions and future research direction are revealed based on the discussed work.

本文研究了带有第二类模糊参数的多目标供应商选择问题。所有涉及的参数（例如总需求，预算分配，配额灵活性，评级值）都被描述为类型2三角模糊（T-2TF）参数。为了解决T-2TF，首先引入基于临界值（CV）的减少方法，然后对机会受限的程序进行建模，以获得清晰的多目标SSP版本。其次，还开发了一种基于间隔的近似方法来对T-2TF参数进行模糊化处理。此外，还提出了一种新颖的交互式中智编程方法来解决确定性多目标SSP，这使决策者可以有效地吸收中立思想或不确定性程度。提出了计算研究以验证和验证去模糊技术和所提出的解决方案方法。还解决了一个选择机会，以最大的总体满意度来选择最理想的折衷解决方案。最后，在讨论的基础上揭示了结论和未来的研究方向。