Garcia-Garcia, G. orcid.org/0000-0001-5562-9197 (2022) Using multi-criteria decision-making to optimise solid waste management. Current Opinion in Green and Sustainable Chemistry, 37. 100650. ISSN 2452-2236
Abstract
Multi-Criteria Decision-Making (MCDM) encompasses a broad range of methods to support decision-making to reach a compromise solution when there are multiple criteria. One example of a multi-criteria problem is identifying the most sustainable solution to manage solid waste. In this case, different conflicting objectives exist, which can be categorised based on environmental, economic, social and technical metrics. In this article, the most relevant MCDM methodologies and tools are described and discussed, focusing on their applicability to assess solid waste management systems. The most relevant methodologies identified are the Analytic Hierarchy Process (AHP), Multi-Attribute Utility Theory (MAUT), Outranking procedures and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). A common weakness of these methodologies is that the evaluation criteria set by decision makers are generally subjective. It is recommended to integrate various methods and tools or to develop bespoke methodologies to optimise solid waste management.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier. This is an author produced version of a paper subsequently published in Current Opinion in Green and Sustainable Chemistry. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Solid waste management; MCDM; AHP; MAUT; PROMETHEE; ELECTRE; TOPSIS |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 26 Jan 2024 13:03 |
Last Modified: | 26 Jan 2024 13:03 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.cogsc.2022.100650 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:208331 |
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