How can I programmatically determine how to fit smaller boxes into a larger package? [closed]

Answer 1

Pisinger is one of the few academics who posts working code. In one of his papers he mentions the "Minimum Depth" problem.

Here is a practical and efficient algorithm for 3D Rectangular Box Packing that adjusts the height of the enclosing box.

And here is an implementation in php.

Answer 2

Metaheuristics are good to deal with real world bin packing problems when there are many packages and/or many constraints. One open source Java implementation is Drools Planner.

Answer 3

After lot of searching i have found a GitHub repository that might help someone. Function PackingService.Pack() takes list of Container and list of Item(s) to be packed as parameter and return result which contains lot of information including

"container(s) packed in percentage and list of packed and unpacked items"

Answer 4

Are you trying to see how many of a single type fits into a particular sized package, or are you trying to mix types as well?

Sounds like you're trying to solve the Knapsack Problem. You might be able to find some algorithms for that which could be adapted to your specific requirements. Just understand that it will be hard to find an efficient algorithm, as the problem is NP complete (though depending on your specific requirements you may be able to find an efficient approximation, or your inputs may be small enough that it doesn't matter).

Answer 5

If the boxes are to be hand packed, then you might consider writing an algorithm which would do what a reasonable human would do. The reason I suggest this is because unless you want to print out packing instructions for each order, then whoever is doing your packing is going to have to workout how they are going to fit the ordered items in however many boxes it has been allocated for the order.

This might then lead to your human packers coming to SO asking on how to programmatically workout how to pack n items into m boxes. :-P (They might also ask you to do it, ask you for instructions, etc).

As long as your algorithm does what a reasonable human being would do, I would personally accept its shipping estimate.

Answer 6

Maybe this will sound obvious, but it might be worthwhile to memoize the problem, then do some of them by hand. Finding a most effecient solution for arbitrary inputs and boxes in NP-hard, but by restricting the problem space, and accepting some inefficiency, that NP size might be something reasonable, and by memoizing, you might be able to bring the "common-case" time down substantially.

It might also help to think about things in terms of hierarchical packing.