Solid Waste Landfill Site Assessment Framework Based on Single-Valued Neutrosophic Hybrid Aggregation and Multi-Criteria Analysis

Wendi Chen, Jiaxing Gu, Shouzhen Zeng and Xiaoying Xie ()
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Wendi Chen: School of Business, Ningbo University, Ningbo 315211, China
Jiaxing Gu: School of Business, Ningbo University, Ningbo 315211, China
Shouzhen Zeng: School of Business, Ningbo University, Ningbo 315211, China
Xiaoying Xie: College of Economics and Management, Zhejiang Normal University, Jinhua 321004, China

Sustainability, 2023, vol. 15, issue 7, 1-21

Abstract: Landfills are an effective way to dispose of waste and appropriate landfill sites can lessen environmental damage during waste treatment. Solid waste landfill site (SWLS) selection has received much attention in the area of multi-criteria decision-making in recent years. However, the uncertainty and complexity of the SWLS selection make it a significant challenge for decision makers (DMs). Since single-valued neutrosophic (SVN) sets have the great advantage of handling complex problems with uncertain and inconsistent information, this paper aims at offering a site planning strategy under the SVN environment. For the SWLS selection problem with interrelated factors, the Schweizer–Sklar power Bonferroni mean operator is first created, which not only considers the possible correlations among attributes but also reduces the adverse effects of anomalous assessment information on decision results. Then, a multi-criteria analysis framework based on the aggregation operator is proposed and then applied to a real-world SWLS selection. DMs can flexibly adjust the parameters in this model to achieve a preferred SWLS that integrates economic, environmental, and social perspectives. The consistent results obtained from the comparative analysis highlight its benefits for selecting proper SWLSs.

Keywords: landfill site selection; Schweizer–Sklar operations; power Bonferroni mean operator; SVN sets; multi-criteria analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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