Repository logo
Log In
Log in as University member:
Log in as external user:
Have you forgotten your password?

Please contact the hohPublica team if you do not have a valid Hohenheim user account (hohPublica@uni-hohenheim.de)
Hilfe
  • English
  • Deutsch
    Communities & Collections
    All of hohPublica
Log In
Log in as University member:
Log in as external user:
Have you forgotten your password?

Please contact the hohPublica team if you do not have a valid Hohenheim user account (hohPublica@uni-hohenheim.de)
Hilfe
  • English
  • Deutsch
  1. Home
  2. Browse by Subject

Browsing by Subject "Real-world application"

Type the first few letters and click on the Browse button
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • Loading...
    Thumbnail Image
    Publication
    Tackling the rich vehicle routing problem with nature-inspired algorithms
    (2022) Lesch, Veronika; König, Maximilian; Kounev, Samuel; Stein, Anthony; Krupitzer, Christian; Lesch, Veronika; University of Würzburg, Würzburg, Germany; König, Maximilian; PASS Logistics Solutions AG, Aschaffenburg, Germany; Kounev, Samuel; University of Würzburg, Würzburg, Germany; Stein, Anthony; University of Hohenheim, Hohenheim, Germany; Krupitzer, Christian; University of Hohenheim, Hohenheim, Germany
    In the last decades, the classical Vehicle Routing Problem (VRP), i.e., assigning a set of orders to vehicles and planning their routes has been intensively researched. As only the assignment of order to vehicles and their routes is already an NP-complete problem, the application of these algorithms in practice often fails to take into account the constraints and restrictions that apply in real-world applications, the so called rich VRP (rVRP) and are limited to single aspects. In this work, we incorporate the main relevant real-world constraints and requirements. We propose a two-stage strategy and a Timeline algorithm for time windows and pause times, and apply a Genetic Algorithm (GA) and Ant Colony Optimization (ACO) individually to the problem to find optimal solutions. Our evaluation of eight different problem instances against four state-of-the-art algorithms shows that our approach handles all given constraints in a reasonable time.

  • Contact
  • FAQ
  • Cookie settings
  • Imprint/Privacy policy