Given n bins of infinite capacity, I want to pack m items into them (each with a specific weight), whilst minimizing the weight of the heaviest bin.
This isn't a traditional bin packing / knapsack problem where a bin has a finite capacity and you attempt to minimize the amount of bins used; I have a set amount of bins and want to use them all in order to make the heaviest bin's weight as low as possible.
Is there a name for this problem? I have looked through a number of papers with key words, but I have found nothing similar.
Cheers.
It's a form of a 2D bin packing problem. The first dimension is a limit on capacity per bin (= hard constraint), the second dimension is to minimize the weight of the heaviest bin (= soft constraint).
With Drools Planner, I 'd start from the cloud balance example and implement it like this: