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Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory

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Abstract

The pollution and emission caused by the manufacturing, operation, and scrapping of marine ships have considerable impact on the environment. Therefore, it is essential to develop an effective and efficient approach toward evaluating the environmental impact of ships. This study uses the green degree of ships concept to evaluate different alternatives. Because environmental evaluation involves several criteria, the problem can be formulated as a traditional multi-criteria decision-making (MCDM) model. In this regard, the main innovation of this study is the development of an improved MCDM model using a novel hybrid method, namely the group fuzzy entropy and cloud technique for order of preference by similarity to ideal solution theory. The developed model calculates the criteria weight and rank based on the selected criteria and alternatives. Finally, a criteria system is developed to evaluate several classical alternatives, and various sensitivity analyses were carried out to validate the robustness of the proposed methodology. The results revealed that the model and criteria system can provide several quantitative and qualitative indicators for governmental policy-makers and agencies, environmental consultants, and environmental service organizations.

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Abbreviations

MCDM:

Multi-criteria decision making

DM:

Decision maker

TOPSIS:

Technique for order of preference by similarity to ideal solution

AHP:

Analytic hierarchy process

ELECTRE:

Elimination et choix traduisant la realité

PROMETHEE:

Preference ranking organization method for enrichment evaluations

VIKOR:

VlseKriterijumska Optimizacija I Kompromisno

DEMATEL:

Decision-making trial and evaluation laboratory

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Acknowledgements

This study was supported in part by the National Natural Science Foundation of China under Grant No. 51775238, Science and Technology Development Project of Jilin Province under Grant Nos. 20180101060JC and 20180101058JC. We also wish to thank the Editor-in-Chief, the associate editor and anonymous reviewers for their constructive and very useful suggestions.

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Authors and Affiliations

  1. The Key Laboratory of High Efficiency and Clean Mechanical Manufacture (Ministry of Education), School of Mechanical Engineering, Shandong University, Jinan, 250061, People’s Republic of China

    Xu Liu & Guangdong Tian

  2. National Demonstration Center for Experimental Mechanical Engineering Education, Shandong University, Jinan, 250061, People’s Republic of China

    Xu Liu & Guangdong Tian

  3. Transportation College, Jilin University, Changchun, 130022, People’s Republic of China

    Xu Liu

  4. Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran

    Amir Mohammad Fathollahi-Fard

  5. Department of Electrical Engineering, École de Technologie Supérieure, University of Québec, Montréal, Canada

    Amir Mohammad Fathollahi-Fard

  6. Faculty of Built Environment, University of New South Wales, Sydney, Australia

    Mohammad Mojtahedi

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  1. Xu Liu
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  4. Mohammad Mojtahedi
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Correspondence to Guangdong Tian.

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Appendix: Supplementary data

Appendix: Supplementary data

See Tables 8, 9, 10, 11, 12, 13, and 14.

Table 8 Uncertainty degree matrix B
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Table 9 Deviation degree matrix C
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Table 10 Fuzzy odd entropy matrix F
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Table 11 Fuzzy dual number matrix D
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Table 12 Interval clouds matrix Y(1) for DM1
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Table 13 Interval clouds matrix Y(2) for DM2
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Table 14 Interval clouds matrix Y(3) for DM3
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Liu, X., Tian, G., Fathollahi-Fard, A.M. et al. Evaluation of ship’s green degree using a novel hybrid approach combining group fuzzy entropy and cloud technique for the order of preference by similarity to the ideal solution theory. Clean Techn Environ Policy 22, 493–512 (2020). https://doi.org/10.1007/s10098-019-01798-7

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