Answers.Body: <p>CSPF provides a good approach- where it's not so complex that you have to tune, based on dijkstra, and it can handle constraints.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-03-19T14:36:23.543Z
Answers.LastActivityDate: 2024-03-19T14:36:23.543Z
Answers.UserDisplayName: Discover
Body: <p>I am looking for a ML Model for route optimization within a factory. I am starting simple with optimizing 1 aisle (2 rows). We have a bunch of criteria, and it would be dependent on the data at that time to create an optimal route. For now I want to stay within 1 aisle, so I don't know if ant colony is the answer. I am looking for a suggestion of which model should I use? RL, GA etc.</p>
  <p>we have a df of shelf, rack, row, item and when it was assigned to come down (starting with just rows 1 and 2)</p>
  <p>The driver can access 2 rows of shipping locations at the same time, and the rows' rack numbers and shelf numbers are aligned with each other . For example, the shipping locations at rack 4 and shelf 3 are accessible for row 1 and row 2 at the same time, as those rows are linked to each other, so the machine driver can get items from those 2 shipping locations at the same exact time.</p>
  <p>Machine max capacity is 60 cf - The items with the highest priority are items with the earliest dock assignment time but if a load is assigned to a dock at a similar time to the earliest dock assignment, and has significantly fewer items than a load with the earlier dock assignment time, prioritize the smaller load.</p>
  <p>Calculate whether the item will fit into the machine in order to be removed from its shipping location. Consider the size of the item and the capacity available in the machine.</p>
  <p>When creating the route, prioritize staying within the same rack number higher than staying within the same shelf number.</p>
  
Tags: <machine-learning>
Title: ML Model for Route Optimization in Manufacturing
UserDisplayName: Discover
ThreadText: # ML Model for Route Optimization in Manufacturing
  
  (Asked by: username_0 on 2024-02-26)
  
  I am looking for a ML Model for route optimization within a factory. I am starting simple with optimizing 1 aisle (2 rows). We have a bunch of criteria, and it would be dependent on the data at that time to create an optimal route. For now I want to stay within 1 aisle, so I don't know if ant colony is the answer. I am looking for a suggestion of which model should I use? RL, GA etc.
  
  we have a df of shelf, rack, row, item and when it was assigned to come down (starting with just rows 1 and 2)
  
  The driver can access 2 rows of shipping locations at the same time, and the rows' rack numbers and shelf numbers are aligned with each other . For example, the shipping locations at rack 4 and shelf 3 are accessible for row 1 and row 2 at the same time, as those rows are linked to each other, so the machine driver can get items from those 2 shipping locations at the same exact time.
  
  Machine max capacity is 60 cf - The items with the highest priority are items with the earliest dock assignment time but if a load is assigned to a dock at a similar time to the earliest dock assignment, and has significantly fewer items than a load with the earlier dock assignment time, prioritize the smaller load.
  
  Calculate whether the item will fit into the machine in order to be removed from its shipping location. Consider the size of the item and the capacity available in the machine.
  
  When creating the route, prioritize staying within the same rack number higher than staying within the same shelf number.
  
  **Tags:** machine-learning
  
  
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  ## 1 answers
  
  ### Answer by username_0 on 2024-03-19. Score: 0
  
  CSPF provides a good approach- where it's not so complex that you have to tune, based on dijkstra, and it can handle constraints.
  
  
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