Im actually working at a startup that wants to use an algorithm to plan transport on large scale. ( Different Industry though). Got any tips or insights on biggest challenges?
The biggest challenges we had were more political. Getting buy-in across the airline as well as _support_ from the airline side to integrate their data and system into ours.
Sadly, it was a people problem, not a tech or algo problem.
So, did you manage to "tackle" the people problem in the end? How did you get them to move and integrate with your system in the end? Was it a bottom up (from the end users) or top down (making it part if company strategy) approach?
Sadly, I don't have these answers. I ended up quitting to go on a long sabbatical.
Last I heard, the airline scrapped the entire project to continue doing things the old way because they felt it was too much work on their end. ¯\_(ツ)_/¯
Does the algo work? Is it better than the status quo and under what circumstances is it susceptible to failure? Does it know when the whole system is over-constrained?
If we assume the algo rocks (because you have operations research veterans), what stage of planning does your system address? What is the experience required and cost of manual intervention?
Fun problem. Human factors and edge cases abound. So much is at stake for a system that already works (to any predictable degree).
The algo works. We have two algorithmic experts onboard, of which one is a professor and one is already working with algos each day (e.g. worked on patients/beds capacity challenge when covid began).
The startup focusses on assigning goods to transport. (As in its not part of the commercial sales process.. only execution of the required capacity planning that comes after it) .Something that has been tried 20 times and failed. It currently is done manually.
