# [DSC Adria 23]Nino Pozar What Are We Shipping.pptx

30 de May de 2023
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### [DSC Adria 23]Nino Pozar What Are We Shipping.pptx

• 1. DSC Adria 2023 Nino Požar Data Scientist & Product Owner, BE-terna +385 91 4007 075 nino.pozar@be-terna.com https://www.linkedin.com/in/nino-pozar WHAT ARE WE SHIPPING – FRESH AIR OR VALUABLE ITEMS?
• 2. 1. Introduction & overview 2. Transportation optimisation 1. The problem 2. Working example 3. Use case example 3. Conclusions Agenda
• 8. The problem Bin packaging problem Knapsack problem Transportation
• 9. Transportation optimisation problem Bin packaging & knapsack problem Bin packaging problem • items of different volumes must be packed into a finite number of bins/containers each of a fixed given volume in a way that minimizes the number of bins used • minimize the number of trucks (containers)
• 10. Transportation optimisation problem Bin packaging & knapsack problem Bin packaging problem • items of different volumes must be packed into a finite number of bins/containers each of a fixed given volume in a way that minimizes the number of bins used • minimize the number of trucks (containers)
• 11. 0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 20 14 20 11 19 4 23 10 3 Transportation optimisation problem Bin packaging & knapsack problem Knapsack problem • given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible • fill trucks with the most valuable items 10 20 12 4 17 14 23 3 14 5 17 50 19 20 10 10 11
• 12. 0 1 2 3 4 5 6 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 8 9 20 14 20 11 19 23 10 3 17 20 14 20 11 19 4 23 10 3 Transportation optimisation problem Bin packaging & knapsack problem Knapsack problem • given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible • fill trucks with the most valuable items 10 20 12 4 17 14 23 3 14 5 17 50 19 20 10 10 11
• 13. 0 1 2 3 4 5 6 0 1 2 3 4 5 6 7 8 2 3 4 5 6 7 8 9 20 14 20 11 19 23 10 17 17 20 14 20 11 19 23 10 3 17 Transportation optimisation problem Bin packaging & knapsack problem Knapsack problem • given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible • fill trucks with the most valuable items 10 20 12 4 17 14 23 3 14 5 17 50 19 20 10 10 11
• 14. 0 1 2 3 4 5 6 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 20 14 20 11 19 23 10 17 17 Transportation optimisation problem Bin packaging & knapsack problem Knapsack problem • given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible • fill trucks with the most valuable items 10 20 12 4 17 14 23 3 14 5 17 50 19 20 10 10 11
• 15. 0 1 2 3 4 5 6 4 5 6 7 8 9 0 1 2 3 4 5 6 Transportation optimisation problem Bin packaging & knapsack problem Knapsack problem • given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible • fill trucks with the most valuable items 23 20 17 14 17 50 20 11 19 10 12 4 3 14 5 10 10
• 17. A A A B A C C B C A A A C C C C 1. First (current) order 2. Next order Order priority 1. A 2. B 3. C Classification priority Ana CFO Dan Warehouse mng Bob Purchaser Round SKUs! A A A A C C B C A A A C C C
• 18. A A A B A C C B C A A A C C C C 1. ROUNDING C 2. Next order Order priority 1. A 2. B 3. C Classification priority 1. First (current) order Ana CFO Bob Purchaser Dan Warehouse mng A A A A C C B C A A A C C C Priority SKUs! Round SKUs!
• 19. C 2. FILL THE TRUCKS A A A B A C C B A A A A A A A C C B C A A A C C C C C C C C C C C C C A A A A A 1. First (current) order 2. Next order Order priority 1. A 2. B 3. C Classification priority Ana CFO Dan Warehouse mng Bob Purchaser Fill 2nd truck! Group SKUs! Priority SKUs! Add truck!
• 20. A A A A A C 3. REARRANGE THE TRUCKS A A A A A C C A A A A A A A C C C B C B A A A C C Ana CFO Dan Warehouse mng Bob Purchaser Group SKUs! Round SKUs! C C C C
• 21. A A A B A C C B A A 3. REARRANGE THE TRUCKS – ROUNDING A A C Ana CFO Dan Warehouse mng Bob Purchaser Round SKUs! Priority SKUs! C C C C C
• 22. A | OOS A A B A C C B A A C A C | OOS C | ALERT C C 3. REARRANGE THE TRUCKS C A A LET'S GO! I’M READY Ana CFO Dan Warehouse mng Bob Purchaser Priority SKUs!
• 23. Bob Purchaser How can AI help Bob? Use case
• 24. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 25. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 26. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 27. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 28. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 29. Bob Purchaser • Bob is presented with results – BI application Presented with results Change & confirm recomm. Reoptimise cargo Check new results Confirm results
• 30. Conclusions? Possibility of controlling incoming orders • Date of expected order arrivals • Date of stock availability Service level is increased • Less delays in production • Less delays in delivery Advantage in managing warehouse • Less jams in warehouses Verification of orders through dashboard • Ability to modify & recalculate • Direct integration with ERP Automation as the ordering procedure is transferred into algorithms of ML platform • Increases productivity • Decreases manual work • Quicker learning curve for new purchasers (replacements) Sustainability effect • Decrease in carbon footprint Financial benefits • Less money spent on transportation
• 31. Thank you! Nino Požar +385 91 4007 075 nino.pozar@be-terna.com https://www.linkedin.com/in/nino-pozar