OBS! Ansökningsperioden för denna annonsen har
A fleet operator typically owns a set of vehicles. When the operator gets a work order it needs to be decided how the order shall be distributed among the vehicles. Each vehicle and/or driver needs also a plan on which locations to visit.
A work order can for example be 1) “move 100 containers between A and B”, 2) “distribute 25 grocery bags to 14 different locations” or “transport 100 post items to 90 persons living at different addresses”.
Example is relatively simple, just find the best route and allocate an adequate number of vehicles”. The other examples are much more tricky. The reason is that the deliver locations can be visited in many different orders.
This master thesis handles the following questions:
How can work orders be broken down to a given set of homogenous vehicles? In this context, homogenous means that the vehicles are equal in goods capacity, energy efficiency etc.
What are adequate measures for doing the work order brake down analysis? Distance and ownership cost are two candidates.
If there are multiple methods available for question 1: what are pros and cons with the methods?
When the work starts up the use case(s), for example post delivery, will be decided.
The thesis work will include various fields such as simulation and optimization. Machine learning is an additional candidate tool. The work will be carried out at Volvo Autonomous Solutions in Gothenburg. The thesis is recommended for one student with programming profile and good mathematical skills.
Don’t hesitate to contact our manager: Dominika Wroblewska, Manager Cloud, +73-902 72 94
Kindly note that due to GDPR, we will not accept applications via mail. Please use our career site.
Thesis Level: Master
Starting date: 9/01/2023
Number of students: 1-2
Jonas Hellgren, Principal Engineer, firstname.lastname@example.org