Distance Approximation for Dynamic Waste Collection Planning

Fabian Akkerman*, Martijn Mes, Wouter Heijnen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
106 Downloads (Pure)


Approximating the solution value of transportation problems has become more relevant in recent years, as these approximations can help to decrease the computational effort required for solving those routing problems. In this paper, we apply several regression methods to predict the total distance of the traveling salesman problem (TSP) and vehicle routing problem (VRP). We show that distance can be estimated fairly accurate using simple regression models and only a limited number of features. We use features found in scientific literature and introduce a new class of spatial features. The model is validated on a dynamic waste collection case in the city of Amsterdam, the Netherlands. We introduce a cost function that combines the travel distance and service level, and show that our model can reduce distances up to 17%, while maintaining the same service level, compared to a well-known heuristic approximation. Furthermore, we show the benefits of using approximations for combining offline learning with online or frequent optimization.

Original languageEnglish
Title of host publicationComputational Logistics - 11th International Conference, ICCL 2020, Proceedings
EditorsEduardo Lalla-Ruiz, Martijn Mes, Stefan Voß
Number of pages15
ISBN (Print)9783030597467
Publication statusPublished - 22 Sep 2020
Event11th International Conference on Computational Logistics, ICCL 2020 - Online conference, Enschede, Netherlands
Duration: 28 Sep 202030 Sep 2020
Conference number: 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference11th International Conference on Computational Logistics, ICCL 2020
Abbreviated titleICCL
Internet address


  • Distance approximation
  • Inventory routing problem
  • Vehicle routing
  • Waste collection
  • 22/2 OA procedure


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