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K-means - Clustering Algorithm - Transportation & Logistics

2074 runs

Added by Continente Siete

Application area: Segmentation, clustering, marketing, logistics, routing

Simulation method: Agent Based, System Dynamics

K-means - Clustering Algorithm

In this agent-based + SD version, you will see one of the most popular segmentation algorithms in action. Visuals will help you understand how it works.

Although the application showed here is focused on image compression, applications for this algorithm ranges from Marketing to Logistics:

-Think of your target population and inherent characteristics in people. How can I group customers in more homogeneous segments so that I can make my targeting more accurate.

-Think of a large routing problem where I have to service different locations. K-means is capable of making groups of locations close to each other so that later a routing algorithm can work within them. This enables to handle a much bigger than usual routing problem.

-Prediction models many times feed on output from k-means algorithms, which enable the creation of new variables.

The model was created with AnyLogic - simulation software / Segmentation, clustering, marketing, logistics, routing

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