An Evolutionary based Decomposition Strategy for the Multi-Depot Heterogeneous Vehicle Routing Problem with Time Windows
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.
|Thesis Advisor||Spliet, R.|
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 http://hdl.handle.net/2105/51983