Zaharudin, Z.A., Brint, A. orcid.org/0000-0002-8863-407X and Genovese, A. orcid.org/0000-0002-5652-4634 (2022) A multi-period model for reorganising urban household waste recycling networks. Socio-Economic Planning Sciences, 84. 101396. ISSN 0038-0121
Abstract
Managing waste is a crucial challenge for modern societies. Within the UK government's ambitious environmental targets, municipal Household Waste Recycling Centres represent key facilities. However, local authority budgets are under severe strain due to reductions in central government funding. Therefore, local councils often need to perform reconfigurations of the recycling centres networks, by reducing the number of sites or their opening hours while still ensuring adequate service levels. This paper describes a novel multi-period mathematical programming model for optimising reorganisational actions within Household Waste Recycling Centre networks. The model is tested on a case study based on an English local authority, in order to demonstrate its applicability to a real-world scenario, and its role in supporting decision-makers in deciding the best way to reorganise Household Waste Recycling Centres.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Reorganisation; Location-allocation; Relocation; Recycling management; Household waste; Circular Economy |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Social Sciences (Sheffield) > Management School (Sheffield) |
Funding Information: | Funder Grant number EUROPEAN COMMISSION - HORIZON 2020 823967 EUROPEAN COMMISSION - HORIZON 2020 101003491 UK RESEARCH AND INNOVATION 10037837 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 26 Sep 2022 09:29 |
Last Modified: | 30 Nov 2022 14:57 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.seps.2022.101396 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:190798 |