Applying quantum approximate optimization to the heterogeneous vehicle routing problem
Licentiate thesis, 2022

Quantum computing offers new heuristics for combinatorial problems. With small- and intermediate-scale quantum devices becoming available, it is possible to implement and test these heuristics on small-size problems. A candidate for such combinatorial problems is the heterogeneous vehicle routing problem (HVRP): the problem of finding the optimal set of routes, given a heterogeneous fleet of vehicles with varying loading capacities, to deliver goods to a given set of customers. This licentiate thesis is an extended introduction to the accompanying paper, which consists of a study of a new formulation of the HVRP applicable to both quantum annealers and programmable noisy intermediate-scale quantum (NISQ) devices.

combinatorial optimization

variational quantum algorithm

Quantum computing

quantum approximate optimization algorithm

vehicle routing

Kollektorn
Opponent: Assistant Professor Evert Van Nieuwenburg from the University of Copenhagen

Author

David Fitzek

Chalmers, Microtechnology and Nanoscience (MC2), Applied Quantum Physics

Subject Categories

Computer and Information Science

Computational Mathematics

Physical Sciences

Vehicle Engineering

Technical report MC2 - Department of Microtechnology and Nanoscience, Chalmers University of Technology: 450

Publisher

Chalmers

Kollektorn

Opponent: Assistant Professor Evert Van Nieuwenburg from the University of Copenhagen

More information

Latest update

6/30/2022