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In operations and supply chains it is not hard to find *A* solution. Operators literally make these decisions manually every day without the need for any comput
by whatever1 3y ago
In operations and supply chains it is not hard to find *A* solution. Operators literally make these decisions manually every day without the need for any computer.
The main challenge is to optimize these decisions. With optimality guarantees. Consistently. Day in, day out, with various uncertainties.
That is what math optimization has been doing for decades.
And no, RL is nowhere to be seen in production, except from some consulting projects that are abandoned.
- vonnik 3y agoOur work was precisely in optimization over massive numbers of possible scenarios amid multi-dimensional uncertainties. Again, significantly outperforms LP. Not surprised that you are an advocate of math optimization. Most people working on optimization in industrial operations and supply chains have an OR background, and this sort of conservatism is common. But there are lots of situations that LP can't optimize while RL can.
- whatever1 3y ago"Again, significantly outperforms LP." No, this is mathematically impossible. You cannot out-optimize a mathematical global optimization solver. Whether that is LP, MILP, or NLP. Exactly because they provide a certificate of optimality. It is like stating that you found a non-negative number that is smaller than 0. It’s not progressive. It’s flat out wrong. "But there are lots of situations that LP can't optimize while RL can" I will be satisfied if you just show us 1. Stay in your lane, and state that you built a fast heuristic that works (finds good solutions but not optimal) in the problems you tried. Nobody can dispute this. But don't make claims you cannot support.
- deleted 3y ago[deleted]