BellmanFord | Parallel Implementation of Bellman Ford Algorithm | GPU library
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Parallel Implementation of Bellman Ford Algorithm
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QUESTION
In XCode it says:Thread 1: EXC_BAD_ACCESS (code=1, address=0x3c000003e7)
...ANSWER
Answered 2020-Apr-23 at 12:51An array is not a pointer, and no amount of casting can change that fact.
*(g+i) (i.e. g[i]) is m[i], which is an int[7], not an int*.
When you interpret its first elements as an address, hilarity ensues.
You need to start with an array of pointers, since that can be converted to a pointer to a pointer.
With minimal changes to your code, it might look like this:
QUESTION
I am trying to read weights from a text file but it's not giving the same output as to when I am setting them manually. This is the data present in the adjlist.txt file:
...ANSWER
Answered 2019-Oct-30 at 03:10Take a closer look at the main parsing loop. For each line read from the file it sets the same value in the weight for all of the nodes.
Example:
QUESTION
I'm trying to find the best possible path in graph using Bellman-Ford algorithm. However, instead of using the sum of all edges to calculate the path length, I want the path with the least casualties. We calculate casualties using this formula: remainingSoldiers = sqrt(a^2 - b^2), where A is our army, B is the enemy army and remainingSoldiers is the number of our soldiers left after the fight.
An example: Let's say we want to conquer city D. We are starting in vertex A with army of strength 100. Our army travels to vertex B, which is patrolled by an enemy army of strength 50. According to our formula, we have 86 soldiers left. Next our army travels to vertex C, so our 86 soldiers fight with 40 soldiers patrolling vertex C, and we have 76 soldiers left. And finally, our 76 soldiers travel to vertex D which is being guarded by 70 enemy soldiers. According to our formula, we conquered the vertex D with 29 soldiers.
So in order to find the best path, we have to calculate which path to take in order to have the least casualties. Hint I got is to set the strength of our army and the strength of the enemy army as weights of edges and use the Bellman-Ford with a modified relaxation algorithm to find the best find path. That's exactly what I did in my code below.
I realized that in order to find the best path, I must find the path with the lowest number of casualties, not the highest number of soldiers left, since finding the path with the highest number is a NP-complete problem.
My code is following (I'm using a custom library for graphs, but it should be really straight-forward and easy to understand):
...ANSWER
Answered 2019-Aug-19 at 21:19I see three problems with your code:
- Storing your starting force in the graph creates ambiguity since you can't tell whether this edge has your forces or enemy's forces as weight. This will be a problem if two cities are connected with each other because you will get double edges. Instead use a variable to store it somewhere in you graph class, in your example
double startingForce = 120; Your call in relax switches between remaining forces and casualties the wrong way around. For calling formula you need your remaining forces, but the output needs to be transformed to casualties again.
QUESTION
I have implemented the Bellman-Ford algorithm to detect negative cycles in a graph. It is worth noting that each edge in the graph has an inverse, so if an edge exists that can go from A -> B, there also exists an edge that can go from B -> A.
My problem is when I am navigating the predecessor chain (stored in the dictionary pred). It seems that the source vertex never has a predecessor, so when I am looping through each vertex in the negative cycle check, an exception is thrown because pred never has an entry for the source vertex.
What does this mean? There seems to be a negative cycle in the graph, but if nothing precedes the source vertex, and the source vertex is "included" in the detected negative cycle, is there really a cycle to begin with?
...ANSWER
Answered 2019-Mar-29 at 15:48To my understanding, the observed behaviour does not indicate a bug in your implementation. The Bellman-Ford algorithm is able to conclude that there is a cycle of negative length; this does not mean that every cycle of negative length can be found. The Floyd-Warshall algorithm might be more suitable for that. Both algorithms solve different formulations of the problem; the first one solves the single-source shortest path problem while the second one solved the all-pairs shotest path problem.
QUESTION
I have something similar to this in Dijkstras algorithm but I’m getting no error in that. I’ve tried substituting different values for the integer max and other various things but nothing works. I’ve also searched the this site and others but found nothing that could help. Also if it makes a difference my graph class is in a class to itself. Any help would be appreciated. I updated my question... question was answered. But I did reformat just in case anyone else wanted to take a look.
...ANSWER
Answered 2018-Dec-11 at 01:25You're declaring the array dist[] with the length of V. And then you're using graph.edge[j].src as an index for the dist[] array. This is why you are getting an ArrayIndexOutOfBoundsException. In short, this means that the src value is bigger than V.
The fix
Increase the length of dist[] by 1.
Inside static void bellmanford(){...}
change from
int dist[] = new int[V];
to
int dist[] = new int[V+1];
This did solve the exception issue for me. But there seem to be more logical issues with the algorithm (The actual problem may be hidden deeper somewhere else.). But at least the program is executing now so you can debug it. Good luck.
QUESTION
I am implementing Bellman ford's algorithm from GeeksForGeeks in Python. I want to generate the Graph(The Diagramatic form and not in dictionary type-which is easy) using some library like pyplot or networkx or something similar. I want the graph UI to contain the nodes,edges and the respective cost.
...ANSWER
Answered 2018-Oct-08 at 17:19If you check this tutorial for networkx, you'll see how easy, is to create a directed graph, plus, plotting it.
Pretty much, It's the same for a directed or simple graph, (API wise), and the plotting, is also simple enough and uses Matplotlib to generate it.
You could make a Tk app, that allows you to input, manually the nodes, and Edges, and store them in ListBoxes, and plot a graph, in function of that, this won't be drag and drop, but still, it helps you visualize the graph on the fly.
and this Matplotlib tutorial, will give you the idea how to embed it in a TK app.
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