New publication in Applied Intelligence [23.11.21]
Christian Krupitzer from the Department of Food Informatics is co-author of the publication "Tackling the Rich Vehicle Routing Problem with Nature-Inspired Algorithms" in Applied Intelligence (Impact Factor: 5.086).
The publication "Tackling the Rich Vehicle Routing Problem with Nature-Inspired Algorithms" by Veronika Lesch (University of Würzburg) with co-authors Maximilian König (PASS Logistics Solutions AG, Aschaffenburg), Samuel Kounev (University of Würzburg), Anthony Stein (Department of Artificial Intelligence in Agricultural Engineering, University of Hohenheim) and Christian Krupitzer (Department of Food Informatics, University of Hohenheim) was published in Springer Applied Intelligence (Impact Factor: 5.086).
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.
The publication is avalaible in SpringerLink.
