A soft-constrained multi-objective facility location approach for designing a network of household waste recycling centres in South Yorkshire

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Sgalambro, Antonino, Fugaro, Serena and Santarelli, Filippo (2025) A soft-constrained multi-objective facility location approach for designing a network of household waste recycling centres in South Yorkshire. Journal of the Operational Research Society. pp. 1-30. ISSN 0160-5682

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Abstract

In the UK Government’s 25 Year Environment Plan, the location of municipal waste collection and recycling facilities plays a crucial role in achieving the Government’s recycling targets. Economic pressures are forcing UK local authorities to reorganise the network of household waste recycling centres (HWRCs) with the dual aim of reducing high operating costs and achieving high user satisfaction, whilst meeting specific legislative requirements. It becomes then paramount to support the optimal design of these networks considering the needs of all the stakeholders involved. We fill this gap by proposing a novel multi-objective facility location problem in waste management (WM) which formalises the underlying real-world scenario for the city of Sheffield in South Yorkshire, and by developing a soft-constrained version of the resulting problem to more accurately capture the actual dynamics driving the network design process. The resulting Pareto Sets are efficiently explored by the robust variant of the AUGMEnted (Formula presented.) -CONstraint method, and a computational characterisation of the proposed model is provided with benchmark instances from a real-world case study. Finally, in-depth scenario and sensitivity analyses provide quantitative and qualitative insights to support strategic planning and decision-making.

Item Type: Article
Additional Information: The authors are grateful to Mr Neil Townrow, Mr Andrew France, Ms Bobbie Gardner, and Mr Alistair Black from the WM Team of the Sheffield City Council for supporting this work by describing and discussing the underlying real-world problem with the authors, and by providing valuable information to generate the dataset utilised in the Case Study. The authors would like to thank the anonymous referees for their valuable comments, which contributed to improving the quality of this article.
Uncontrolled Keywords: augmented ε-constraint,case study,location,multi-objective optimisation,soft constraints,waste management,modelling and simulation,strategy and management,statistics, probability and uncertainty,management science and operations research,sdg 11 - sustainable cities and communities,sdg 12 - responsible consumption and production ,/dk/atira/pure/subjectarea/asjc/2600/2611
Faculty \ School: Faculty of Social Sciences > Norwich Business School
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Depositing User: LivePure Connector
Date Deposited: 15 May 2026 12:50
Last Modified: 15 May 2026 12:50
URI: https://ueaeprints.uea.ac.uk/id/eprint/103043
DOI: 10.1080/01605682.2025.2537885

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