Uncertainty in Real-World Vehicle Routing (Extended Abstract)
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00141880" target="_blank" >RIV/00216224:14330/25:00141880 - isvavai.cz</a>
Result on the web
<a href="https://ojs.aaai.org/index.php/SOCS/article/view/36013" target="_blank" >https://ojs.aaai.org/index.php/SOCS/article/view/36013</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1609/socs.v18i1.36013" target="_blank" >10.1609/socs.v18i1.36013</a>
Alternative languages
Result language
angličtina
Original language name
Uncertainty in Real-World Vehicle Routing (Extended Abstract)
Original language description
The motivation for our research arises from the limitations of traditional deterministic heuristic solvers for vehicle routing problems (VRP) observed in industrial practice. In general, the quantities provided to the solvers as inputs, e.g., loads or service times, are typically estimates or simplifying reflections of reality. While current state-of-the-art solvers are applicable to complex VRP variants at scale, their inability to reason about uncertainties limits their usefulness in real-world applications. Despite stochastic VRPs being a widely studied topic, related approaches are typically centered around the uncertainty in the problem rather than extending successful deterministic methods. Moreover, uncertainty-related methodologies and models are often strongly linked to computationally expensive sampling or exact algorithms making their scaling problematic. Thus, we aim for easy-to-integrate, reusable, and especially computationally efficient mechanisms, allowing us to naturally extend state-of-the-art heuristic solvers for a wide range of VRPs with reasoning about input uncertainties. We formulate four mechanisms fitting these criteria, including standard chance constraints, two data manipulation methods, and a novel penalty-based method. These four mechanisms are compared and analyzed for the most common sources of uncertainty in loads and times on both benchmark and complex real-world instances. Their favorable scaling properties are demonstrated on instances with up to 1,000 customers.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
18th International Symposium on Combinatorial Search, SoCS 2025
ISBN
9781577359012
ISSN
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e-ISSN
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Number of pages
2
Pages from-to
269-270
Publisher name
AAAI Press
Place of publication
Washington, DC, USA
Event location
Glasgow, United Kingdom
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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