What are the limitations of shortest path algorithms?

What are the limitations of shortest path algorithms?

Shortest path algorithms, like Dijkstra's and A*, have limitations such as high computational cost in large graphs and inability to handle dynamic changes efficiently.

Can you explain why they struggle with dynamic graphs?

Sure! Dynamic graphs change over time, and most shortest path algorithms are designed for static graphs, requiring recalculation for each change.

Are there any algorithms that handle dynamic graphs better?

Yes, algorithms like Dynamic Shortest Path and Contraction Hierarchies are designed to handle dynamic changes more efficiently.

What about their performance in real-world applications?

In real-world applications, performance can vary based on graph size and density, but heuristics can improve efficiency in many cases.

What are some practical examples of these algorithms in use?

Common examples include GPS navigation systems, network routing protocols, and urban traffic management systems.