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Intuitionistic Unbalanced Linguistic Generalized Multiple Attribute Group Decision Making and Its Application to Green Products Selection

Author

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  • Bing Han
  • Zhifu Tao
  • Huayou Chen
  • Ligang Zhou

Abstract

In many countries, green products play a critical role in energy recycling and environment protection. The selection of green products can be regarded as a multiple attribute decision making (MADM) problem. Due to the complexity and uncertainty of the problem, decision makers may give their personal preference values to different attributes of alternatives by intuitionistic unbalanced linguistic term sets. The main purpose of this paper is to put forward a new generalized multiple attribute group decision making (GMAGDM) approach based on the intuitionistic unbalanced linguistic dependent weighted generalized Heronian mean (IULDWGHM) operator and the intuitionistic unbalanced linguistic dependent weighted generalized geometric Heronian mean (IULDWGGHM) operator. The proposed method can not only relieve the influence of unfair assessments, but also consider the interaction effects of attributes. Furthermore, the appropriate parameter values and operators can be selected to meet the different risk preference of decision makers and actual requirements. Finally, a green products selection case is given to illustrate the effectiveness and universality of the developed approach.

Suggested Citation

  • Bing Han & Zhifu Tao & Huayou Chen & Ligang Zhou, 2018. "Intuitionistic Unbalanced Linguistic Generalized Multiple Attribute Group Decision Making and Its Application to Green Products Selection," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-24, October.
  • Handle: RePEc:hin:jnlmpe:4620310
    DOI: 10.1155/2018/4620310
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