A modified ELECTRE II method with double attitude parameters based on linguistic Z-number and its application for third-party reverse logistics provider selection

Applied Intelligence(2022)

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摘要
As more attention is given to environmental protection, sustainable development has become a hot topic for the international community and the companies are motivated to focus on reverse logistics (RL) in their operations for resource conservation and sustainability. However, many enterprises are limited by their economic strength and resources so that outsourcing RL to third-party reverse logistics provider (3PRLP) is their best choice. Therefore, how to effectively assess and select the 3PRLP has been a crucial issue. Given that the preference and optimism of decision makers (DMs) should be exhibited, in this paper, an improved ELECTRE II method with double attitude parameters under linguistic Z-number (LZN) environment is proposed to deal with such decision problems. Firstly, the LZN is in use to describe experts’ assessments as well as the reliability of evaluations qualitatively. Then an improved ELECTRE II model based on ideal point method is presented to rank alternatives accurately, in which the main concept of ideal point method is pressed into service in determining the preference levels of alternatives and identifying the outranking relations. Meanwhile, two attitude parameters are introduced, which can express DMs’ preference for risk as well as profit and their optimism for decision making, thereby making the decision process more practical and the ranking more reasonable. Then a numerical example on the selection of 3PRLP is shown to minutely explain procedures of the presented method and a sensitivity analysis on the double attitude parameters is conducted to illustrate effects of the two indexes and verify the robustness of the proposed method. Finally, some comparisons are carried out to prove its effectiveness and meliority.
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关键词
Third-party reverse-logistics provider selection,Linguistic Z-numbers,ELECTRE II,Attitude parameters,Multi-attribute decision-making
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