Vehicle Routing: Less “Artificial”, More “Intelligence”

The integration of multiple constraints of the Vehicle Routing Problem (VRP) variants is computationally expensive. Although vehicle routing problems have been well researched, variants are typically treated in isolation, whereas industry requires integrated solutions. Solution algorithms are also tested using benchmark data that are questionable, and that do not represent typical applications. The paper proposes an approach that solves a problem by analyzing its environment through cluster analysis, chooses an appropriate solution strategy, and tests the results in an attempt to learn for the purposes of improved future decisions.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/1845641795
• Corporate Authors:

  WIT Press

  Ashurst Lodge
  Ashurst, Southampton  United Kingdom  SO40 7AA
• Authors:
  • Joubert, J W
• Conference:
  • Urban Transport XII. Urban Transport and the Environment in the 21st Century
  • Location: Prague , Czech Republic
  • Date: 2006-7-12 to 2006-7-14
• Publication Date: 2006-7

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References;
• Pagination: pp 245-256
• Monograph Title: Urban Transport XII. Urban Transport and the Environment in the 21st Century

Subject/Index Terms

• TRT Terms: Algorithms; Artificial intelligence; Benchmarks; Cluster analysis; Decision making; Heuristic methods; Learning; Routing; Vehicles
• Uncontrolled Terms: Metaheuristics
• Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01037415
• Record Type: Publication
• ISBN: 1845641795
• Files: TRIS
• Created Date: Nov 28 2006 11:31AM