I have a sea of weighted nodes with edges linking clusters of nodes together. This graph follows the typical small world layout.
I wish to find a path finding algorithm, which isn't costly on processor power, to find a path along the best possible path where the nodes are the most favorably weighted, the fastest route is not the most important factor. This algorithm, also takes into consideration load bearing, and traffic rerouting.
(sidenote: could neural networks be used here?)
Thanks
I'm looking at ACO. Is there anything better than ACO for this kind of problem?
Right the A* algorithm finds the least cost or fastest route, without load balancing.
Lets say that the fastest or shortest route is not the most important route, what is more important is following a path where the weighted nodes have a certain value. no1.
no2. If using A* the traffic on that route gets overloaded then suddenly that path is redundant. So as cool as A* is, it doesnt have certain features that ACO ie inherent load balancing.
-- unless im mistaken and misunderstood A*
Then what beats ACO?
It really looks like a show down between ACO and A* , there has been so much positive talk about A* , I will certainly look deeper into it.
Firstly in response to David; I can run ACO simulation in the back ground and come up with the best path, so yes there is an initial startup cost but the startup luckily isnt essential. So i can afford to run a simulation multiple times. The one real trouble is finding connected source and destination nodes. Whereas it seems A* will be able to do this quite easily. Now what happens when this network get dreadfully large like in millions of nodes. Will A* be able to scale easily?
I will research A* further. But I leave you with a last question!
Will A* be able to scale as well as Antnet (ACO)?