Fast constructive heuristics for the uncapacitated inventory routing problem

The inventory routing problem (IRP) poses a significant optimization challenge across various industries. This paper focuses on the uncapacitated IRP, by introducing fast constructive heuristics integrating insights from approximation algorithms, particularly rounding techniques in linear programmin...

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Veröffentlicht in:Journal of heuristics Jg. 31; H. 2; S. 23
Hauptverfasser: Alarcón, Miguel Ángel Marfurt, Pedrosa, Lehilton Lelis Chaves, Usberti, Fábio Luiz
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.06.2025
Springer Nature B.V
Schlagworte:
Algorithms
Approximation
Artificial Intelligence
Calculus of Variations and Optimal Control; Optimization
Distribution costs
Effectiveness
Heuristic
Heuristic methods
Inventory
Linear programming
Management Science
Mathematics
Mathematics and Statistics
Operations Research
Operations Research/Decision Theory
Optimization
Routing
Approximation algorithms
Linear programming
Inventory routing
Heuristic algorithms
Branch-and-cut
ISSN:1381-1231, 1572-9397
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Zusammenfassung:The inventory routing problem (IRP) poses a significant optimization challenge across various industries. This paper focuses on the uncapacitated IRP, by introducing fast constructive heuristics integrating insights from approximation algorithms, particularly rounding techniques in linear programming (LP). The proposed heuristics efficiently deliver effective solutions, providing advantages over methods such as branch-and-cut and metaheuristics. Methodologically, we emphasize scalability, subjecting our algorithms to rigorous stress tests with larger instances. Computational experiments, utilizing 420 instances, demonstrate the effectiveness and scalability of our heuristics, notably those tailored to specific problem variants, achieving an average gap of 2.2%. Our work underscores the effectiveness of leveraging approximation algorithms for the uncapacitated IRP, with future directions aimed at enhancing heuristics for broader real-world applicability, including the capacitated version of the IRP.
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ISSN:1381-1231
1572-9397
DOI:10.1007/s10732-025-09558-1