Nowadays planners of (larger) logistic service providers face the challenge of optimizing the use of assets (trucks) while also taking into account a variety of constraints such as in time pickup, in time delivery, conditions in which cargo must be transported in combination with the available assets to transport cargo. In time pickup and delivery has a lot to do with when customers want transport to be executed. This may lead to highs and lows in need for assets to do the transport. On top of that it often happens that assets drive empty. Because of the lack time and functionality in the tooling environment to try out options, planners make an unlucky choice for reloading and routing and in some cases transport becomes less economic.

At this moment planners are often not aware of how many empty drives they have, how to avoid peaks and lows, unlucky reload moments, etc. Planners also do not have the tooling environment to see the effect of their planning activities. They just make a choice that adheres best to the constraints for that transport. The planners do not have the overview if the choice they made optimizes the transport at hand but makes other transport significantly more expensive.

What planners need is a tooling environment that challenges them and that allows them to execute several alternatives in planning. By playing with alternatives such as speeding up or delaying pickup and delivery of cargo, planners get a better feeling for avoiding high and lows in asset usage. When a better overview is created, planners can pick the best elements from every planning alternative. Moreover, since the tooling environment considers all transport, the danger of making choices that are sub-optimal becomes less.

This assignment is the first in a series to get to a gamified environment for planning transport. It comprises the following questions:

  1. What are the constraints in planning transport?
  2. What are effects that make transport more or less economic?
  3. When considering the constraint and effects, how do they influence each other?
  4. When considering the influences, what are the approaches to leverage them?

Besides a report that describes the work, the final aim (that might go beyond this first bachelor graduation assignment) is to have as end result:

  1. Tools that help analyze data.
  2. Algorithm describe how constraints and effects influence each other.
  3. Implementation of the algorithm.

This assignment is supervised by:

  • Dasko Koel- and Vriestransporten: a logistic service provider that has its main office in Almelo
  • NexusZ, a developer of netcentric software systems in Hengelo

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