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The video presentation from the author is approachable even for a non-domain expert. It looks like this has pretty broad applicability to applications in chemical processes, scheduling, logistics (pick ups and drop offs along the route), re-fueling, etc.

I think @DropPanda gave a great example of regenerative charging in an EV.

In the video the author does use cost/price-function terminology.

Djikstra doesn't handle negative weights, Bellman-Ford is optimal for positive edge only. This apparently is also easier to parallelize.

The Quanta article mentioned below is excellent https://www.quantamagazine.org/finally-a-fast-algorithm-for-...




> Bellman-Ford is optimal for positive edge only.

???

CLRS says it takes negative weight edges (just no negative cycles) and does it in O(VE). I have no idea where you're getting this from


>Bellman-Ford is optimal for positive edge only

What do you mean “optimal”? The Bellman-Ford algorithm gives you the shortest path, period.




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