Order (changes) forecast and assignment – Van den Bosch



Company Name / Department Van den Bosch
Contact Person Teun Franssen
 Location Erp
Optional remote work Yes, at least two days / week at the office
Travel expenses (own account or reimbursed by the company) Reimbursed by the company
Housing arranged by company No
Housing expenses (how much per month, own account or subsidized by the company) Own account
Internship compensation  €500,- per month
Study program
ESCF community


Start date

September, 2023


Company Description

Van den Bosch is an international logistics service provider located in Erp, The Netherlands. They aim to drive sustainable and reliable change in the supply chain through intelligent innovation. More than 80% of all their transport is performed by means of intermodal transport. They believe that logistics is not just about transport, but also about data, insights, and know-how. They are constantly trying to drive change within the sector, which is why they are known as “The Supply Changer in Bulk”.


Project Description

Project description:

We receive lots of orders every day. For each order we can have the following three options:

  1. Accept the order with own equipment
  2. Accept and trade the order
  3. Reject the order

We would like to have an algorithm that automatically decides what to do with an order and for the orders that are performed with our own equipment, what equipment type will be used for the order.

Between receiving and executing an order, the orders are changed many times. Every change leads to extra work for the customer service and planning. We would like to know whether we can expect changes for an order.

Goals of the project:

Automatically decide what to do for orders, based on the already received and expected orders for the coming 2 weeks.

Determine the probability that an order will change and what changes to expect.


    1. Order forecast for the coming weeks.
    2. An algorithm that decides what to do with an order.
    3. Create an algorithm that determines what orders are likely to change.
    4. Determine the order details that are likely to change. 

    Essential student knowledge:

    Machine Learning/AI – Logistics – Integer programming




    More information: escf@tue.nl  


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