# Category: Data Structures

## Graph Data Structure – Python Implementation

Today, as data volumes are growing almost exponentially, search in artificial intelligence and computer science is regaining it’s popularity. There is basically no field without application of at least some of the search algorithms. Many of these search algorithms in computer science and artificial intelligence rely heavily on graphs and trees as underlying data structure ...

## A Star (A*) Algorithm with Caching – Java Implementation

Route calculation is computationally an expensive operation. There are several ways how to reduce computational load on the backend. I’ll show you how I optimized my computational resources. There are times where a bunch of people is heading to the same event using the same or at least similar paths. Following this logic, it is ...

## A Star (A*) Algorithm Implementation in Java

A* algorithm can be seen as an heuristic extension of Dijkstra’s. Whereas in the Dijkstra’s priority-queue ordering is based only on the distance from the start node to the current, A* algorithm additionally calculates the distance from the current node to the goal-node. Thus the ordering in the priority queue is different and the algorithm ...

## Dijkstra’s Algorithm implementation in Java

The Breadth First Search (BFS) algorithm basically checks only if there is a path from node A to node B. It’ doesn’t necessarily find the shortest path between two graph nodes. Here comes Dijkstra into the game. Dijkstra’s algorithm finds the shortest possible route between two graph nodes. The main difference between Dijkstra and BFS ...

## Searching neighbors in Graph Data Structure by matrix multiplication

Which vertices in graph can be reached in 1, 2 or N hops? This can basically be implemented in two ways. First, if the graph is implemented as adjacency matrix, by checking connections (ones in double array or a row) and iterating further. Second, if the graph structure is implemented as ArrayList, by checking lists of ...