Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems

Vehicle Routing Problems (VRP) are computationally challenging, constrained optimization problems, which have central role in logistics management. Usually different solvers are being developed and applied for different kind of problems. However, if descriptive and general features could be extracted to describe such problems and their solution attempts, then one could apply data mining and machine learning methods in order to discover general knowledge on such problems. The aim then would be to improve understanding of the most important characteristics of VRPs from both efficient solution and utilization points of view. The purpose of this article is to address these challenges by proposing a novel feature analysis and knowledge discovery process for Capacitated Vehicle Routing problems (CVRP). Results of knowledge discovery allow the authors to draw interesting conclusions from relevant characteristics of CVRPs.

• Record URL:
  • https://doi.org/10.1007/978-3-030-37752-6
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030377519
• Supplemental Notes:
  • © Springer Nature Switzerland AG 2020.
• Corporate Authors:

  Springer Cham

  Gewerbestrasse 11
  Cham,   Germany 
• Authors:
  • Kärkkäinen, Tommi
  • Rasku, Jussi
• Publication Date: 2020-2

Language

• English

Media Info

• Media Type: Web
• Edition: 1st Edition
• Features: References;
• Pagination: pp 77-102
• Monograph Title: Computation and Big Data for Transport: Digital Innovations in Surface and Air Transport Systems
• Serial:
  • Computational Methods in Applied Sciences
  • Volume: 54
  • Publisher: Springer Cham
  • ISSN: 1871-3033
  • Serial URL: https://www.springer.com/series/6899

Subject/Index Terms

• TRT Terms: Data mining; Delivery vehicles; Machine learning; Optimization; Routes and routing; Vehicle capacity
• Subject Areas: Data and Information Technology; Freight Transportation; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01892601
• Record Type: Publication
• ISBN: 9783030377519
• Files: TRIS
• Created Date: Sep 11 2023 11:39AM