MATLAB Implementation of D Method Using Dijkstra's Algorithm

This document presents an implementation approach for D Method, a variation of Dijkstra's algorithm, using MATLAB. The implementation includes a main function example illustrating the complete workflow. However, the documentation could be enhanced by explaining specific problem domains where D Method and Dijkstra's algorithm are applicable, such as network routing or graph-based pathfinding. Additional technical details should cover time and space complexity analysis - Dijkstra's algorithm typically achieves O(V^2) time complexity with adjacency matrices or O(E + V log V) with priority queues. The implementation could demonstrate graph type adaptability (sparse vs. dense graphs) through different matrix representations. For algorithm selection guidance, consider comparing D Method with alternatives like A* algorithm (with heuristics) or Bellman-Ford (for negative weights). The code structure should include: graph initialization using adjacency matrices, distance array initialization with Infinity values, priority queue implementation for node selection, and relaxation procedures for updating shortest paths. Extended code examples should showcase: 1) Basic shortest path calculation between nodes 2) Path reconstruction using predecessor arrays 3) Handling of disconnected graphs with proper error handling 4) Performance comparison between standard Dijkstra and D Method variations through runtime measurements.