  Current world trade is based and supported in a strong and healthy supply
chain, where logistics play a key role in producing and providing key assets
and goods to keep societies and economies going. Current geopolitical and
sanitary challenges faced in the entire world have made even more critical the
role of logistics and increased demands for tuning transport function to keep
the supply chain up and running. The challenge is only increasing and growing
for the future, thus tackling transport optimization provides both business and
social value. Optimization problems are ubiquitous and they present a challenge
due to its complexity, where they're typically NP-hard problems. Quantum
Computing is a developing field, and the Quantum Annealing approach has proven
to be quite effective in its applicability and usefulness to tackle
optimization problems. In this work we treat the Vehicle Routing Problem, which
is also a variation of a famous optimization problem known as the Traveling
Salesman Problem. We aim to tackle the vehicle optimization problem from the
last mile logistic scenario application, with a perspective from the classical
and quantum approaches, and providing a solution which combines both, also
known as hybrid solution. Finally, we provide the results of the analysis and
proposal for the consideration of applications in a near term business case
scenario.
