Combinatorial Optimization with LLMs/Transformers
I am curious whether a well-designed Transformer can do something like a job-shop-scheduling problem (JSSP) at the high level as GA and other heuristical approaches.The logic I am coming from is that words are sequences, and JSSP can be transformed into a sequence of tasks no matter what the precedence graph looks like. And final solution would be set of tasks, as LLM makes a set of words that make a story…I did find some literature on this, but problems are usually very small - like few dozens of tasks with very simple/streamlined rules.
2023-06-05T14:43:29Z
Yes I’d be very interested in this as well
2023-06-15T21:20:09Z
Does the data in JSSP scale up now, like millions pieces of job shop schedules?
2023-07-25T04:02:21Z
I’m interested in LLM4CO too! Could you share the literature about the topic please ?
2024-01-23T02:51:47Z
me too.  Here are  some related papers found recently. But I am doubting about the promissing performance since LLMs are not that controllable:[2310.19046] Large Language Models as Evolutionary Optimizers(ICLR24-Google DeepMind)[2309.03409] Large Language Models as Optimizers
2024-08-30T07:33:46Z
Check this updating list (GitHub - FeiLiu36/LLM4Opt: A Collection on Large Language Models for Optimization) on LLM4Opt including combinatorial optimization and other related worksHere is an ICML Oral paper on LLM4CO (GitHub - FeiLiu36/EoH: Evolution of Heuristics)