A novel multi-criteria decision-making framework for selecting municipal solid waste management alternative with...

Area of Science:

• Environmental Engineering
• Operations Research
• Decision Sciences

Background:

• Municipal solid waste management (MSWM) presents complex multi-criteria decision-making (MCDM) challenges due to inherent uncertainties.
• Traditional MCDM methods struggle with ambiguous linguistic data and ensuring decision consistency.

Purpose of the Study:

• To develop a novel MCDM framework for selecting optimal MSWM scenarios under a 2-dimensional uncertain linguistic (2-DUL) environment.
• To enhance decision-making effectiveness and efficiency by addressing uncertainty and ensuring matrix consistency.

Main Methods:

• Utilized a 2-DUL set to represent decision-maker preferences, incorporating linguistic evaluations and assessment reliability.
• Employed an expectation reduced-dimension technique for handling 2-DUL sets.
• Integrated Best-Worst Method (BWM) with Analytic Network Process (ANP) for consistent criteria weighting.
• Applied an extended QUALIFLEX approach for ranking MSWM scenarios based on weighted concordance/discordance.

Main Results:

• The proposed framework successfully handles both cardinal and ordinal information in MSWM scenarios.
• A case study in Beijing demonstrated the framework's feasibility and efficiency in selecting an optimal MSWM scenario.
• Comparative analysis confirmed the superiority of the developed MCDM framework.

Conclusions:

• The novel MCDM framework provides a robust and efficient solution for complex MSWM scenario selection.
• The approach effectively manages uncertainty and improves the reliability of decision-making in waste management.
• This study offers a valuable tool for policymakers and practitioners in optimizing MSWM strategies.