Distance Approximation for Dynamic Waste Collection Planning

Martijn Mes, Wouter Heijnen, Fabian Akkerman

Research output: Working paper

160 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 eort 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 accurately using simple regression models and only a limited number of features. We use features found in scientific literature and introduce a new class of geographical 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 oine learning with online or frequent optimization.
Original languageEnglish
Number of pages15
Publication statusSubmitted - 15 May 2020


Dive into the research topics of 'Distance Approximation for Dynamic Waste Collection Planning'. Together they form a unique fingerprint.

Cite this