Green port performance evaluation under uncertainty: a multiple attribute group decision analysis

With respect to multiple attribute group decision making problems with linguistic information of attribute values, a group decision analysis is proposed. Some new aggregation operators are proposed: the 2-tuple linguistic weighted harmonic averaging (TWHA), 2-tuple linguistic ordered weighted harmonic averaging (TOWHA) and 2-tuple linguistic combined weighted harmonic averaging (TCWHA) operator and properties of the operators are analyzed. Then, a method based on the TWHA and TCWHA operators for multiple attribute group decision making is presented. In this approach, alternative appraisal values are calculated by the aggregation of 2-tuple linguistic information. Thus, the ranking of alternative or selection of the most desirable alternative(s) is obtained by the comparison of 2-tuple linguistic information. Finally, a numerical example is used to illustrate the applicability and effectiveness of the proposed method.

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Integrating multiple criteria decision analysis and production theory for performance evaluation Framework and review

European Journal of Operational Research ◽

10.1016/j.ejor.2021.05.046 ◽

2021 ◽

Author(s):

Harald Dyckhoff ◽

Rainer Souren

Keyword(s):

Performance Evaluation ◽

Decision Analysis ◽

Multiple Criteria ◽

Evaluation Framework ◽

Multiple Criteria Decision Analysis ◽

Production Theory

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Public Transportation Hub Location with Stochastic Demand: An Improved Approach Based on Multiple Attribute Group Decision-Making

Discrete Dynamics in Nature and Society ◽

10.1155/2015/430109 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

Sen Liu ◽

Zhilan Song ◽

Shuqi Zhong

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Public Transportation ◽

Group Decision ◽

Numerical Study ◽

Hub Location ◽

Hub Location Problem ◽

The Public ◽

Multiple Attribute ◽

Qualitative Factors

Urban public transportation hubs are the key nodes of the public transportation system. The location of such hubs is a combinatorial problem. Many factors can affect the decision-making of location, including both quantitative and qualitative factors; however, most current research focuses solely on either the quantitative or the qualitative factors. Little has been done to combine these two approaches. To fulfill this gap in the research, this paper proposes a novel approach to the public transportation hub location problem, which takes both quantitative and qualitative factors into account. In this paper, an improved multiple attribute group decision-making (MAGDM) method based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and deviation is proposed to convert the qualitative factors of each hub into quantitative evaluation values. A location model with stochastic passenger flows is then established based on the above evaluation values. Finally, stochastic programming theory is applied to solve the model and to determine the location result. A numerical study shows that this approach is applicable and effective.

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CPT-MABAC method for spherical fuzzy multiple attribute group decision making and its application to green supplier selection

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-202954 ◽

2021 ◽

pp. 1-11

Author(s):

Huiyuan Zhang ◽

Guiwu Wei ◽

Xudong Chen

Keyword(s):

Decision Making ◽

Group Decision Making ◽

Supplier Selection ◽

Group Decision ◽

Comparison Method ◽

Entropy Method ◽

Decision Makers ◽

Green Supplier Selection ◽

Multiple Attribute ◽

Psychological Perceptions

The green supplier selection is one of the popular multiple attribute group decision making (MAGDM) problems. The spherical fuzzy sets (SFSs) can fully express the complexity and fuzziness of evaluation information for green supplier selection. Furthermore, the classic MABAC (multi-attributive border approximation area comparison) method based on the cumulative prospect theory (CPT-MABAC) is designed, which is an optional method in reflecting the psychological perceptions of decision makers (DMs). Therefore, in this article, we propose a spherical fuzzy CPT-MABAC (SF-CPT-MABAC) method for MAGDM issues. Meanwhile, considering the different preferences of DMs to attribute sets, we obtain the objective weights of attributes through entropy method. Focusing on the current popular problems, this paper applies the proposed method for green supplier selection and proves for green supplier selection based on SF-CPT-MABAC method. Finally, by comparing existing methods, the effectiveness of the proposed method is certified.

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