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"Ben Jackson" wrote in message
news:tCmbd.121529$He1.75934@attbi_s01... I keep meaning to apply Dijkstra's algorithm to airway routing. The key will be choosing edge costs. I tried something similar for Western Europe. Thinking aloud... My algorithm was basically: a) load the entire airway network as a graph using distances as costs b) link airports to the network using SIDs and STARs (important in Europe, probably less so in US) c) add preferred routes using the a cost of start_to_end_great_circle_distance * factor, where factor is just less than 1. d) run Dijkstra's algorithm (I was doing this in Perl so I just used the Graph module from CPAN) for a departure airport e) store the least cost routing from the departure airport to everywhere else in a database Repeat for other departure airports of interest. Processing time for one departure airport for my network was about 30s on a fairly typical desktop machine. YMMV, literally. ;-) Provided your airway network only changes every 28 days (can't speak for the US but that's what happens in the rest of the world for aeronautical data), you've then got "static" routes valid for a month which means that to run this for 100 airports or so, it should be a case of "do the calculation once and store the results". You can do this all with appropriate costs assigned to the routes and transitions that you want. The tricky part is weighting thoses costs properly against whatever you consider to be overriding factors (eg forecast winds, icing, aircraft performance, distance, available nav equipment, ...) Adding dynamic issues is not only difficult from a "what cost factor do I use?" point of view, but actually affects the entire strategy. Calculating weighted factors based on winds means that you have to do a calculation for the entire network (you may be able to preload the network, but you still have to run a weighting factor calc for each edge) which is likely to be very time consuming. You then have to run Dijkstra's algorithm to get the least-cost routes. But now we're doing that for *every* flight, which means that we wait for both steps of the processing (edge costs + Dijkstra) instead of doing a database lookup on stuff that's run once a month. I wondered about a middle ground. If you could store the 10 or even 100 least-cost routes for a particular airport-pair, then running those routes for a single flight would be relatively quick (either individually or doing Dijkstra on the much reduced network). But Dijkstra doesn't produce the runners up, only the winner, so how do we find the set of 10 or 100 routes to consider? Do you knock out legs and run the algorithm again? If so, which ones? Reducing the network to waypoints within x miles of the great circle for a particular flight (a little like Paul Tomblin's suggestion) is one possibility, but, at least in Europe, x would have to be pretty big. On a 3 hour trip to Germany from my home base in the UK, I basically have the choice between an initial route that goes east over Holland, or south and then south east over Belgium. For a 450 mile route, I have to consider a band of possibilities at least 150 miles wide. Anyway, just sharing some thinking. Julian Scarfe |
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