In this episode, we take another look, a fresh perspective on Data Science for Logistics. In earlier episodes, we talked about related topics like Forecasting and crafting a Picking Algorithm using Data Science.

With the guests of this episode, we dive into two specific challenges in the warehousing domain, the cost-based selection is the first one and the second is put-away with simulation as the red line.

During the recording, we found out that our guests have a big dream: realizing the Digital Twin of the bol.com fulfilment centre. But at the same time, they are very practical and they explain how they started with the two examples and how this will eventually add up to the digital twin.What this episode coversTo speak with them:It would be very nice to create a digital twin of the warehouse to simulate the whole warehouse to create not local but a global optimum.GuestsChristianne Wisse – Data Scientist at bol.com and a professional doctorate in engineering at the Jheronimus Academy of Data Science (JADS)Charles de Leau – Data Scientist @ bol.com with an interesting background in Logic (BA, MA Philosophy), Statistics/Science (Bsc, MSc Criminology) and Data science (National University of Singapore). He previously worked as a consultant in Sydney, Singapore and the Netherlands.NotesDigital Twin - how wiki explains thisThe simulation of the put-away mechanism. It represents one zone in the fulfilment centre. Every green tile represents one closet. The greener it gets the higher the volume in that closet.(Image: https://cdn.sanity.io/images/qxrxmo3r/techlab-prd/5824c3f2d24d53b361c91cc10e315caf303385bf-500x500.gif)

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