Click on the link above for a live demo. Visualize how search algorithms traverse through a graph with walls and weighted edges. Dijkstra's algorithm guarantees the shortest possible path (optimal cost path). The A* algorithm will also determine the shortest path while incorporating a heuristic function (more efficient). The heuristic estimates the cost of the cheapest path from the current node (denoted as 'n') to the goal, thereby reducing the amount of neighbors visited and finding the shortest path in less time than Dijkstra's. Greedy best first search only use the heuristic function which will always choose the current shortest cost edge.
Depth first search
Breadth first search
Greedy best first search
Dijkstra's algorithm
A* search algorithm
Click and drag start node (green) or finish node (red) to move its position.
Shift click to create or remove a wall node (black).
Shift click to add/remove weight (double cost) to/from a node (pink).
Option to recursively generate a maze. Sometimes the generator will produce a non-solvable maze.
Clean up options:
Reset Graph: resets all path (yellow), visited (gray), and neighbor nodes(light green).
Clear Weights: clears all weight nodes.
Clear Walls: clears all wall nodes.
Clear Graph: clear all node types except for the start and end nodes.
g(n) = cost of the path from the start node to n.
h(n) = heuristic function that estimates the cost of the cheapest path from n to the finish node.
Dijkstra's: f(n) = g(n)
A*: f(n) = g(n) + h(n)
Greedy best first search: f(n) = h(n)
git clone https://github.com/nellogan/PathfindingVisualizer
npm install
npm run start-dev
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