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Comparison of heuristic and machine learning algorithms for a multi-objective vehicle routing problem
University of Skövde, School of Informatics.
University of Skövde, School of Informatics.
2024 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The vehicle routing problem is an optimisation problem with a high computational complexity that can be solved using heuristics methods to achieve near-optimal solutions in a reasonable amount of time. The work done in this study aims to compare the execution time and distance of different routing engines when using VROOM, as well as evaluate different implementations of the k-means algorithm by looking at the rand- and adjusted rand index. The results show a difference in the distance and execution time depending on which routing engine is used and it is unclear if there is a difference in the k-means implementations. Investigating the cause behind the observed results would be interesting in future works.   

Place, publisher, year, edition, pages
2024. , p. 47, xxvii
Keywords [en]
Vehicle routing problem, real-world problem, heuristics, optimisation, solving tool, k-means, VROOM-project
National Category
Information Systems, Social aspects
Identifiers
URN: urn:nbn:se:his:diva-24041OAI: oai:DiVA.org:his-24041DiVA, id: diva2:1875552
Subject / course
Informationsteknologi
Educational program
Computer Science - Specialization in Systems Development
Supervisors
Examiners
Available from: 2024-06-23 Created: 2024-06-23 Last updated: 2024-06-23Bibliographically approved

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • apa-cv
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf