Minimum Weight Spanning Tree in Operational Research
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A minimum weight spanning tree (MST) connects all vertices in a connected graph with the least total edge weight and no cycles, with Prim’s and Kruskal’s algorithms being common methods to find it. MSTs have applications in image processing, network design, and cluster analysis, providing advantages like simpler network design and cost savings, but also carry disadvantages such as no backup paths and limitations in network types. The document outlines these concepts along with their pros and cons.
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Minimum Weight Spanning Tree in Operational Research
- 2. MINIMUM WEIGHT SPANNING TREE PAGE 02 A minimum weight spanning tree (MST) is a subset of edges in a connected graph that connects all vertices without cycles and has the smallest possible total edge weight.
- 3. ALGORITHMS There are two algorithms to find minimum spanning tree. 1 Prim’s Algorithm 2 Kruskals Algorithm PAGE 03
- 5. ADVANTAGES . & DISADVANTAGES Here are some advantages and disadvantages of minimum weight spanning tree. SIMPLER NETWORK DESIGN USEFUL IN MANY FIELDS COST SAVINGS NO BACKUP PATHS NOT ALWAYS BEST FOR EVERY PROBLEM LIMITED TO CERTAIN TYPES OF NETWORK DISADVANTAGES PAGE 05 ADVANTAGES