Compare QAOA with quantum annealing to optimize electric vehicle charging on motorways
By Anmol
This research aims to address the issue of scheduling the charging electric motor vehicles (EMV) on motorways. It uses two effective quantum optimization algorithms: quantum approximate optimization algorithm (QAOA) and quantum annealing (QA). The cost function will consider the following factors in order to optimize experience for drivers on roads: distance between charging station and starting point, chargers available, available power at charger, vehicle speed (corresponds to larger power usage), EMV battery capacity, energy in EMV battery, charging time per charger, traffic density, charging station capacity, and predicted demand of charging stations at a given time. Currently, I am focusing on QAOA and applying it to the MaxCut problem, a similar optimization problem also considered NP-hard. This is the step leading to the implementation of QAOA in the EMV situation.