Evaluating Dijkstra’s Algorithm vs. A* Algorithm

Dijkstra’s algorithm and A* (A-star) are both popular algorithms used for pathfinding and graph traversal. While they share similarities, they are often chosen based on specific requirements and scenarios in navigation and routing tasks.

Overview of A* Algorithm

A* is a pathfinding and graph traversal algorithm that aims to find the shortest path between two nodes in a graph. It is an extension of Dijkstra’s algorithm that incorporates heuristics to improve efficiency. The key feature of A* is its use of a heuristic function to estimate the cost from the current node to the destination, allowing it to prioritize paths that seem more promising, potentially reducing the number of nodes it needs to explore.

How A* Works

A* algorithm operates by maintaining two primary costs for each node:

1. G-cost: The exact cost of the path from the start node to the current node.

2. H-cost: The heuristic cost, which is an estimated cost from the current node to the destination node. The heuristic must be admissible, meaning it never overestimates the true cost to reach the destination.

A* calculates the F-cost for each node as the sum of the G-cost and H-cost:

• F-cost = G-cost + H-cost

The algorithm prioritizes exploring nodes with the lowest F-cost, using the heuristic to guide the search towards the destination. By integrating this heuristic, A* often finds the shortest path more quickly than Dijkstra’s algorithm, especially in large graphs.