When AI Packs Too Much Hype: Reassessing LLM 'Discoveries' in Bin Packing
A warehouse manager, a cloud scheduler, and a container-ship planner all know the same unpleasant truth: fitting things into limited capacity is where tidy strategy goes to die. That is why bin packing remains such a useful test case. The problem is easy to explain and difficult to solve optimally. Items arrive. Bins have fixed capacity. The objective is to use as few bins as possible. In the online version, the system must decide where to place each item as it arrives, without seeing the future. This is not just a toy puzzle. It resembles production scheduling, memory allocation, server placement, freight consolidation, and every other operational setting where tomorrow’s workload has the bad manners not to disclose itself in advance. ...