• Media type: E-Article
  • Title: Two-stage stochastic integrated adjustment deviations and consensus models in an asymmetric costs context
  • Contributor: Li, Huanhuan; Ji, Ying; Qu, Shaojian
  • Published: IOS Press, 2021
  • Published in: Journal of Intelligent & Fuzzy Systems, 40 (2021) 6, Seite 12301-12319
  • Language: Not determined
  • DOI: 10.3233/jifs-210443
  • ISSN: 1064-1246; 1875-8967
  • Keywords: Artificial Intelligence ; General Engineering ; Statistics and Probability
  • Origination:
  • Footnote:
  • Description: Decision-makers usually have a variety of unsure situations in the environment of group decision-making. In this paper, we resolve this difficulty by constructing two-stage stochastic integrated adjustment deviations and consensus models (iADCMs). By introducing the minimum cost consensus models (MCCMs) with costs direction constraints and stochastic programming, we develop three types of iADCMs with an uncertainty of asymmetric costs and initial opinions. The factors of directional constraints, compromise limits and free adjustment thresholds previously thought to affect consensus separately are considered in the proposed models. Different from the previous consensus models, the resulting iADCMs are solved by designing an appropriate L-shaped algorithm. On the application in the negotiations on Grains to Green Programs (GTGP) in China, the proposed models are demonstrated to be more robust. The proposed iADCMs are compared to the MCCMs in an asymmetric costs context. The contrasting outcomes show that the two-stage stochastic iADCMs with no-cost threshold have the smallest total costs. Moreover, based on the case study, we give a sensitivity analysis of the uncertainty of asymmetric adjustment cost. Finally, conclusion and future research prospects are provided.