In this thesis we decompose a large Vehicle Routing Problem with multiple depots, a heterogeneous fleet and customers with time windows. The process, which we call 'multi-process route optimiza­tion', first splits the VRP over smaller sub-problems and then solves these sub-problems simultaneously using multiple processors. The goal is to obtain solutions of similar quality in substantially less time. We develop an evolutionary based decomposition method with a fitness function that considers both the running time and solution quality. Computational experiments on real world problem instances show that solutions can be obtained in substantially less time. After a few iterations we can even obtain better solutions than without decomposition. After a few iterations of splitting and solving, we alternate our splitting method with the Sweep method to create more diversity in our splits.

Additional Metadata
Thesis Advisor Spliet, R.
Persistent URL
Series Econometrie
Puttelaar, R. van den. (2020, April 16). An Evolutionary based Decomposition Strategy for the Multi-Depot Heterogeneous Vehicle Routing Problem with Time Windows. Econometrie. Retrieved from