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A Dynamic Decision Making Method Based on GM(1,1) Model with Pythagorean Fuzzy Numbers for Selecting Waste Disposal Enterprises

Author

Listed:
  • Peng Li

    (College of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Ju Liu

    (College of Economics and Management, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Cuiping Wei

    (College of Mathematical Sciences, Yangzhou University, Yangzhou 225002, China)

Abstract

With the rapid development of society and the economy, most cities have to face a serious problem of “Garbage Siege”. The garbage classification is imperative because the traditional disposal method for household solid waste is not suitable for this situation. The Chinese government proposed a public private partnership (PPP) style to increase the efficiency of garbage disposal in 2013. An effective method to evaluate the waste disposal enterprises is essential to choose suitable ones. A reasonable evaluation method should consider enterprises’ performance not only now but also in the future. This paper aims to propose a dynamic decision making method to evaluate the enterprises’ performance based on a GM(1,1) model and regret theory with Pythagorean fuzzy numbers (PFNs). First, we proposed a GM(1,1) model for predicting score function of PFNs. Then, we put forward a method to obtain the prediction of grey degree using OWA operator. Based on the prediction of score function and grey degree, we established a novel GM(1,1) model of PFNs. Furthermore, we utilized the grey incidence method to obtain the criteria weights with Pythagorean fuzzy information. We used the regret theory to aggregate information and rank the alternatives. Finally, we applied our proposed method to solve the selecting waste disposal enterprises problem in Shanghai. By the case study we can obtain that our method is effective to solve this problem.

Suggested Citation

  • Peng Li & Ju Liu & Cuiping Wei, 2019. "A Dynamic Decision Making Method Based on GM(1,1) Model with Pythagorean Fuzzy Numbers for Selecting Waste Disposal Enterprises," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5557-:d:274655
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    References listed on IDEAS

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    1. Wei Meng & Daoli Yang & Hui Huang, 2018. "Prediction of China’s Sulfur Dioxide Emissions by Discrete Grey Model with Fractional Order Generation Operators," Complexity, Hindawi, vol. 2018, pages 1-13, January.
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    3. Reimann, Olivier & Schumacher, Christian & Vetschera, Rudolf, 2017. "How well does the OWA operator represent real preferences?," European Journal of Operational Research, Elsevier, vol. 258(3), pages 993-1003.
    4. Zeng, Bo & Duan, Huiming & Bai, Yun & Meng, Wei, 2018. "Forecasting the output of shale gas in China using an unbiased grey model and weakening buffer operator," Energy, Elsevier, vol. 151(C), pages 238-249.
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    Cited by:

    1. Xiaoyun Zhang & Jie Bao & Shiwei Xu & Yu Wang & Shengwei Wang, 2022. "Prediction of China’s Grain Consumption from the Perspective of Sustainable Development—Based on GM(1,1) Model," Sustainability, MDPI, vol. 14(17), pages 1-11, August.
    2. Xueguo Xu & Tingting Xu & Meizeng Gui, 2020. "Incentive Mechanism for Municipal Solid Waste Disposal PPP Projects in China," Sustainability, MDPI, vol. 12(18), pages 1-16, September.
    3. Aijun Liu & Maurice Osewe & Huixin Wang & Hang Xiong, 2020. "Rural Residents’ Awareness of Environmental Protection and Waste Classification Behavior in Jiangsu, China: An Empirical Analysis," IJERPH, MDPI, vol. 17(23), pages 1-12, December.

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