directed-acyclic-graphs

I have a graph with an s and t vertex that I need to find the shortest path between. The graph has a lot of special properties that I would like to capitalize on: The graph is a DAG (directed acyclic graph). I can create a topological sort in O(|V|) time, faster than the traditional O(|V + E|). Within the topological sort, s is the first item in the list and t is the last. I was told that once I have a topological sort of the vertices I could find the shortest path faster than my current standard of Dijkstra's Uniform Cost, but I cannot seem to find the algorithm for it. Pseudo code would be

I have a DAG. I have this operation to add a edge between two nodes. If A is reachable from B, then B is A's parent. If A is reachable from B without going though another node, then B is A's direct parent. Requirements for this graph are: No cycles. For any node, there is a list of direct parents P[1],P[2],P[3]... P[i] is not a parent of P[j] for any i and j. If adding a edge, requirement 1 is not met, the edge is not constructed. If adding a edge, requirement 2 is not met, the edge is constructed, but the direct parents will be modified in a way such that requirement 2 is met. For example,

I want an algorithm that gives one instance of a cycle in a directed graph if there is any. Can anyone show me a direction? In pseudo-code, or preferably, in Ruby? I previously asked a similar question , and following the suggestions there, I implemented Kahn's algorithm in Ruby that detects if a graph has a cycle, but I want not only whether it has a cycle, but also one possible instance of such cycle. example_graph = [[1, 2], [2, 3], [3, 4], [3, 5], [3, 6], [6, 2]] Kahn's algorithm def cyclic? graph ## The set of edges that have not been examined graph = graph.dup n, m = graph.transpose ##

Good Morning. I'm trying to setup a DAG too Watch/sense for a file to hit a network folder Process the file Archive the file Using the tutorials online and stackoverflow I have been able to come up with the following DAG and Operator that successfully achieves the objectives, however I would like the DAG to be rescheduled or rerun on completion so it starts watching/sensing for another file. I attempted to set a variable max_active_runs:1 and then a schedule_interval: timedelta(seconds=5) this yes reschedules the DAG but starts queuing task and locks the file. Any ideas welcome on how I could

Here is my problem: I have a sequence S of (nonempty but possibly not distinct) sets s_i, and for each s_i need to know how many sets s_j in S (i ≠ j) are subsets of s_i. I also need incremental performance: once I have all my counts, I may replace one set s_i by some subset of s_i and update the counts incrementally. Performing all this using purely functional code would be a huge plus (I code in Scala). As set inclusion is a partial ordering, I thought the best way to solve my problem would be to build a DAG that would represent the Hasse diagram of the sets, with edges representing

I am currently researching for my next project. This is in a pre-planning phase so this question is just to get an overview on existing technology. Setup I have a directed acyclic graph (DAG) with multiple inputs and output, think artificial neuronal network for now: The common way to process such a structure is to process the whole network on every (time-)step. I believe that is the method used by frp libraries such as netwire . Now I am in the fortunate position that I have a stream of events that each presents the change in one of the input nodes. The idea is that I probably don't have to