19-02-2019 – Evoluon
On Tuesday the 19th of February, Data2Move community members gathered at the Evoluon in Eindhoven for a brand new Data2Move event. After events on Collaboration and Data Driven Inventory, this event revolved around the topic of transportation. Themed Data Driven Last Mile, the objective was to show the participants how different variables affect transportation and in particular, how data can help enhance transport planning decisions.
After a delicious lunch, Prof. Luuk Veelenturf opened the event by introducing the programme of the day. However, there was no time to sit back and relax for too long because the first part of the scheduled workshop called everyone into action. The goal of this workshop? To show the participants how they can use data to increase the quality of their transportation decisions.
Workshop Part I: Travel Time Data Analysis
Before the workshop started Veelenturf shared the results of the guessing exercise that was part of the registration procedure for the event. Every participant had to make an educated guess on the registration form of the event regarding the average speed of a truck on the Dutch road during its delivery route with intervals of two hours. The winner, Mr. Ingmar Scholten (CTAC), had an impressive score of 59%. Could the use of the data driven approach beat this excellent score…?
At the start of the workshop Veelenturf briefly addressed the planning of delivery routes (routing) and how some routes may take longer depending on factors such as length, weather, time of the day and day of the week. After this, the participants were divided into small teams of four to five people. Based upon a large dataset of truck delivery routes (including speed, time and distance) the different teams had to predict the average speed within a two hour time window starting from 6:00 until 18:00 and a time-window for delivery that would best match those average speeds. This input was then compared to the data of approximately a thousand random pre-picked routes. Each prediction was assessed by calculating the percentage of trips that actually arrived within the time window that a company gave to its customers based on forecasted speeds and the time window setting.
All of the teams were supervised by a BSc/MSc/Phd/PDEng student with access to the dataset. It was up to the partners to discuss and think of ways to filter the data and come to average speeds and a suitable time window for delivery. The students were equipped with a pre-programmed tool to aid the process. Most teams came to suitable average speeds. However, the winning team of this first part of the workshop did not succeed in beating Mr. Scholtens’ score…..yet. The question remained whether this score would be beaten at all in the second part of the workshop.
Keynote by Stefan Minner (TU Munich) on Routing with Uncertain Travel and Service Times
When one was under the impression that after the exciting first part of the workshop they could finally sit back and let someone else do the work, they were most certainly wrong. The keynote by Prof. Stefan Minner was very engaging but challenging. Minner talked about a Data-Driven approach for routing of delivery services under uncertain travel and service times. Most models use deterministic travel and service times but according to Minner this produces incomplete results in practice. Minner pointed out how machine learning can be applied to logistics and transportation. He also addressed the difference between predictive analytics (sequential approach) and prescriptive analytics (integrated approach) and pointed out that a significant increase in forecasting accuracy does not always necessarily leads to a significant increase in performance. In conclusion Minner explained the data driven approach to the vehicle routing problem with time windows and showed some computational results and numerical tests of this approach. After this, it was time for a well-deserved coffee break and some network opportunities.
Workshop Part II: One last time to improve your estimates
After the break, the results of the first workshop were highlighted in the second part of the workshop. Veelenturf shared some of the results of a study done by one of his students on the same dataset. This student had come to 18 different speed profiles based upon differences in distance, urbanisation and day of the week. By using these profiles, the student managed to predict travel speeds that accounted for almost 90% of routes arriving within the specified time window. Based on this prediction this student also managed to optimise the truck planning using software developed by TU/e.
Inspired by this example, the teams then got a chance to improve their scores by making different speed profiles based upon distance. So every team had to produce speed profiles and a time window, but now they also had to choose three different distance categories for different speed profiles.
Compared to the initial guesswork and the results of the first part of the workshop, each team showed a large increase in their on-time scores. This shows that further exploration of the data and the determination of more profiles by setting parameters was beneficial to the on-time scores. A powerful conclusion to illustrate the importance of good data analytics and critical thinking.
After all this data-crunching it was finally time to announce the winning team. Every team-member received a small device that enables you to track your own speed throughout the day. We will have to find out at the next event if the results of their personal speed tracking are just as impressive as their prediction accuracy.
The theme featured in this Data2Move event was transportation. The topic of the upcoming Data2Move event in May is Customer Sensing and Responding. This next event will feature a number of on-going student projects (Bachelor and Master). Students will share the valuable insights they have discovered and there is room to give them your input as a professional. As Customer Sensing and Responding is the last charter, this means that for the event after May, we, as a community, can go in any direction we want. Please do not hesitate to share your ideas about possible topics.