Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem

<p dir="ltr">This paper addresses the Two-Stage Capacitated Facility Location Problem (TSCFLP), a challenging optimization problem with significant applications in supply chain network design. The need for effective solution methods arises from the problem’s large-scale complexity an...

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المؤلف الرئيسي: Denis Alicic (23073484) (author)
مؤلفون آخرون: Nurettin Sezer (14778217) (author), Miroslav Marić (23073487) (author), Raka Jovanovic (17947838) (author)
منشور في: 2025
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author Denis Alicic (23073484)
author2 Nurettin Sezer (14778217)
Miroslav Marić (23073487)
Raka Jovanovic (17947838)
author2_role author
author
author
author_facet Denis Alicic (23073484)
Nurettin Sezer (14778217)
Miroslav Marić (23073487)
Raka Jovanovic (17947838)
author_role author
dc.creator.none.fl_str_mv Denis Alicic (23073484)
Nurettin Sezer (14778217)
Miroslav Marić (23073487)
Raka Jovanovic (17947838)
dc.date.none.fl_str_mv 2025-10-06T09:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2025.3616111
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Matheuristic_Fixed_Set_Search_Applied_to_the_Two-Stage_Capacitated_Facility_Location_Problem/31168912
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Commerce, management, tourism and services
Transportation, logistics and supply chains
Engineering
Manufacturing engineering
Mathematical sciences
Numerical and computational mathematics
Adaptive greedy algorithm
facility location problem
matheuristics
metaheuristic
Genetic algorithms
Benchmark testing
Search problems
Vehicle dynamics
Transportation
Synthetic data
Robustness
dc.title.none.fl_str_mv Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">This paper addresses the Two-Stage Capacitated Facility Location Problem (TSCFLP), a challenging optimization problem with significant applications in supply chain network design. The need for effective solution methods arises from the problem’s large-scale complexity and the strong influence of spatial and capacity constraints on solution quality. We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. Computational experiments on standard benchmark instances show that MFSS is highly competitive with state-of-the-art methods, while demonstrating improved robustness by consistently reaching high-quality solutions across multiple runs. In addition, this work introduces geographically realistic instances—beyond the synthetic datasets used in previous research—and demonstrates that these experiments reveal regional cost dependencies and spatial utilization patterns, underscoring the practical value of MFSS in supporting real-world distribution network design. Overall, the findings emphasize that the main strength of MFSS lies in its flexible architecture, which combines solution quality, consistency, and ease of adaptation to related facility location variants.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3616111" target="_blank">https://dx.doi.org/10.1109/access.2025.3616111</a></p>
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identifier_str_mv 10.1109/access.2025.3616111
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/31168912
publishDate 2025
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spelling Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location ProblemDenis Alicic (23073484)Nurettin Sezer (14778217)Miroslav Marić (23073487)Raka Jovanovic (17947838)Commerce, management, tourism and servicesTransportation, logistics and supply chainsEngineeringManufacturing engineeringMathematical sciencesNumerical and computational mathematicsAdaptive greedy algorithmfacility location problemmatheuristicsmetaheuristicGenetic algorithmsBenchmark testingSearch problemsVehicle dynamicsTransportationSynthetic dataRobustness<p dir="ltr">This paper addresses the Two-Stage Capacitated Facility Location Problem (TSCFLP), a challenging optimization problem with significant applications in supply chain network design. The need for effective solution methods arises from the problem’s large-scale complexity and the strong influence of spatial and capacity constraints on solution quality. We propose a twofold contribution: first, an adaptive greedy algorithm that generates high-quality initial solutions, achieving markedly better results than traditional constructive heuristics at comparable computational costs; and second, the adaptation of the Matheuristic Fixed Set Search (MFSS) to the TSCFLP. Computational experiments on standard benchmark instances show that MFSS is highly competitive with state-of-the-art methods, while demonstrating improved robustness by consistently reaching high-quality solutions across multiple runs. In addition, this work introduces geographically realistic instances—beyond the synthetic datasets used in previous research—and demonstrates that these experiments reveal regional cost dependencies and spatial utilization patterns, underscoring the practical value of MFSS in supporting real-world distribution network design. Overall, the findings emphasize that the main strength of MFSS lies in its flexible architecture, which combines solution quality, consistency, and ease of adaptation to related facility location variants.</p><h2 dir="ltr">Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2025.3616111" target="_blank">https://dx.doi.org/10.1109/access.2025.3616111</a></p>2025-10-06T09:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2025.3616111https://figshare.com/articles/journal_contribution/Matheuristic_Fixed_Set_Search_Applied_to_the_Two-Stage_Capacitated_Facility_Location_Problem/31168912CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/311689122025-10-06T09:00:00Z
spellingShingle Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
Denis Alicic (23073484)
Commerce, management, tourism and services
Transportation, logistics and supply chains
Engineering
Manufacturing engineering
Mathematical sciences
Numerical and computational mathematics
Adaptive greedy algorithm
facility location problem
matheuristics
metaheuristic
Genetic algorithms
Benchmark testing
Search problems
Vehicle dynamics
Transportation
Synthetic data
Robustness
status_str publishedVersion
title Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
title_full Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
title_fullStr Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
title_full_unstemmed Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
title_short Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
title_sort Matheuristic Fixed Set Search Applied to the Two-Stage Capacitated Facility Location Problem
topic Commerce, management, tourism and services
Transportation, logistics and supply chains
Engineering
Manufacturing engineering
Mathematical sciences
Numerical and computational mathematics
Adaptive greedy algorithm
facility location problem
matheuristics
metaheuristic
Genetic algorithms
Benchmark testing
Search problems
Vehicle dynamics
Transportation
Synthetic data
Robustness