Green material selection for sustainability: A hybrid MCDM approach

Area of Science:

• Materials Science
• Environmental Engineering
• Industrial Engineering

Background:

• Green material selection is critical for sustainable development in the material industry.
• Multi-criteria decision making (MCDM) challenges arise from subjective criteria and conflicting goals in green material selection.
• Existing methods often lack a comprehensive approach to address these complexities.

Purpose of the Study:

• To propose a novel hybrid MCDM approach for optimal green material selection.
• To integrate Decision Making and Evaluation Laboratory (DEMATEL), Analytical Network Process (ANP), Grey Relational Analysis (GRA), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS).
• To provide a robust decision support tool for sustainable material selection based on product requirements.

Main Methods:

• Developed a hybrid MCDM framework combining DEMATEL, ANP, GRA, and TOPSIS.
• Formulated a nonlinear programming model with constraints to calculate an integrated closeness index.
• Validated the approach through an empirical case study on rubbish bin material selection.

Main Results:

• The proposed hybrid MCDM method successfully identified the optimal green material for the case study.
• Sensitivity analysis confirmed the accuracy and stability of the results.
• The integrated approach outperformed existing methods in decision support.

Conclusions:

• The hybrid MCDM approach offers a more accurate and effective tool for green material selection.
• This method enhances the ability to evaluate alternatives and select sustainable strategies.
• It addresses the inherent subjectivity and conflicting criteria in green material selection processes.