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I once had to work on code to do this[2] (place had different sized boxes for shipping, they wanted them used efficiently) which had its own extra constraints (

I once had to work on code to do this[2] (place had different sized boxes for shipping, they wanted them used efficiently) which had its own extra constraints (certain items had to be on top, in specific rotations; etc.) but that was based on [1]. Maybe it would have been easier using the EB-AFIT algorithm. [1] Optimizing Three-Dimensional Bin Packing Through Simulation, https://www.researchgate.net/publication/228974015_Optimizing_Three-Dimensional_Bin_Packing_Through_Simulation https://www.researchgate.net/publication/228974015_Optimizin... [2] It was not a fun time because there was no pipeline from the product database to this service which meant it was frequently out of date re: dimensions, weight, packing position requirements, etc. which drove the warehouse packers mad but after three months of my asking for, if nothing else, a daily CSV download being rebuffed, I quit.

matsemann 3y ago
Worked on something similar, with similar constraints as to products not being able to be placed freely, for instance something heavy could crush something brittle. Also, dimension data is forever a problem. Additionally, that data doesn't reflect reality even when it's fairly accurate, since things are seldom perfect cuboids. So assuming that leaves lot of unused room in reality = not optimal. For instance something in a similar packaging to a bag of ships or dog food, is thinner in the ends than in the middle, and possibly malleable in shape. Also a real life constraint is that it has to be possible to actually pack. Expecting a packer to follow complicated instructions to a T for it to work, or else it wont fit, will never work. Additionally, things can arrive in a certain order, which needs to be accounted for if packing should happen before all items are ready. I think it's a cool problem to work on. So much to think about outside just the algorithmic perfect world scenario.

matsemann 3y ago

Worked on something similar, with similar constraints as to products not being able to be placed freely, for instance something heavy could crush something brittle. Also, dimension data is forever a problem. Additionally, that data doesn't reflect reality even when it's fairly accurate, since things are seldom perfect cuboids. So assuming that leaves lot of unused room in reality = not optimal. For instance something in a similar packaging to a bag of ships or dog food, is thinner in the ends than in the middle, and possibly malleable in shape. Also a real life constraint is that it has to be possible to actually pack. Expecting a packer to follow complicated instructions to a T for it to work, or else it wont fit, will never work. Additionally, things can arrive in a certain order, which needs to be accounted for if packing should happen before all items are ready. I think it's a cool problem to work on. So much to think about outside just the algorithmic perfect world scenario.