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The Balanced Facility Location Problem: Complexity and Heuristics.

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Τίτλος: The Balanced Facility Location Problem: Complexity and Heuristics.
Συγγραφείς: Schmidt, Malena1 (AUTHOR) malenaschmidt2000.ls@gmail.com, Singh, Bismark2 (AUTHOR) b.singh@southampton.ac.uk
Πηγή: INFORMS Journal on Computing. Jan/Feb2026, Vol. 38 Issue 1, p16-38. 23p.
Θεματικοί όροι: *Heuristic, *Simulation methods & models, Quadratic assignment problem, Location problems (Programming), Combinatorial optimization, Sustainability
Γεωγραφικοί όροι: Bavaria (Germany)
Περίληψη: A recent work proposes a new quadratic facility location model to address ecological challenges faced by policymakers in Bavaria, Germany. Building on this, we significantly extend our understanding of this new problem. We develop connections to traditional combinatorial optimization models and show that the problem is NP hard. We then develop several classes of easy-to-implement heuristics to solve this problem. These are rooted in solving special cases of the generalized quadratic assignment problem as a subproblem; this subproblem is also NP hard. On moderate-sized instances from Bavaria—that were previously intractable—our proposed heuristics compute feasible solutions that are 0.5% (on average) improved over the generic solution method in just over a minute (on average), even when the generic solver runs for 20,000 seconds. Larger instances show an improvement of 5% (on average) compared with the generic solution method in an average of 410 seconds. History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis. Funding: B. Singh was partially supported by the University of Southampton [Research Investment and Support Building Sustainable and Green Futures Program]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2024.0693) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2024.0693). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]
Copyright of INFORMS Journal on Computing is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: The Balanced Facility Location Problem: Complexity and Heuristics.
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  Data: A recent work proposes a new quadratic facility location model to address ecological challenges faced by policymakers in Bavaria, Germany. Building on this, we significantly extend our understanding of this new problem. We develop connections to traditional combinatorial optimization models and show that the problem is NP hard. We then develop several classes of easy-to-implement heuristics to solve this problem. These are rooted in solving special cases of the generalized quadratic assignment problem as a subproblem; this subproblem is also NP hard. On moderate-sized instances from Bavaria—that were previously intractable—our proposed heuristics compute feasible solutions that are 0.5% (on average) improved over the generic solution method in just over a minute (on average), even when the generic solver runs for 20,000 seconds. Larger instances show an improvement of 5% (on average) compared with the generic solution method in an average of 410 seconds. History: Accepted by Pascal Van Hentenryck, Area Editor for Computational Modeling: Methods & Analysis. Funding: B. Singh was partially supported by the University of Southampton [Research Investment and Support Building Sustainable and Green Futures Program]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2024.0693) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2024.0693). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of INFORMS Journal on Computing is the property of INFORMS: Institute for Operations Research & the Management Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        Type: general
      – SubjectFull: Simulation methods & models
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      – SubjectFull: Quadratic assignment problem
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      – SubjectFull: Location problems (Programming)
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      – SubjectFull: Combinatorial optimization
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      – SubjectFull: Sustainability
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      – SubjectFull: Bavaria (Germany)
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      – TitleFull: The Balanced Facility Location Problem: Complexity and Heuristics.
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              Text: Jan/Feb2026
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              Y: 2026
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