@revista_internacional{1032,
  keywords = {Multiple attribute group decision-making, Probabilistic linguistic term set, Consensus reaching, Mixed integer programming},
  author = {Peng Wu and Zhiyuan Jiang and Jinpei Liu and Ligang Zhou and Luis Martínez},
  title = {A mixed integer programming driven consensus reaching process for multi-attribute group decision-making under probabilistic linguistic environment},
  abstract = {With the rise of e-commerce, live streaming has emerged as a powerful tool. The type of anchor affects consumers’ decisions in live streaming, and the selection of anchor type has uncertainty. Gathering information in the context of multi-attribute group decision-making (MAGDM) is crucial for obtaining more reliable results when decisions are defined under uncertainty. In this scenario, the use of probabilistic linguistic term sets (PLTS) has proven to be a versatile way of conveying information, allowing decision makers (DMs) to effectively elicit qualitative information by considering probability distributions. However, in many instances involving group decision-making processes, DMs often struggle to reach a consensus. This paper studies MAGDM problem under probabilistic linguistic information based on least common multiple expansion (LCME) principle and mixed integer programming. Firstly, the LCME principle is introduced to normalize PLTS with different lengths and a new distance measure of PLTSs is proposed based on this principle. Subsequently, a mixed integer programming driven consensus reaching process (CRP) is proposed, including two consensus measures (individual and group). Then, a probabilistic linguistic MAGDM (PL-MAGDM) approach is presented by integrating the LCME principle and CRP. After that, the proposed approach is applied to anchor type selection. Finally, sensitivity analysis and comparative analysis are conducted to demonstrate the viability of the approach. Our study has two key contributions. One is to propose a new distance measure with LCME principle and CRP under PLTSs environment, the other is to propose a PL-MAGDM approach, which can assist companies in selecting anchors for operation management.},
  year = {2025},
  journal = {Computers & Industrial Engineering},
  volume = {206},
  pages = {111191},
  issn = {0360-8352},
  url = {https://www.sciencedirect.com/science/article/pii/S0360835225003377},
  doi = {https://doi.org/10.1016/j.cie.2025.111191},
}