Minimum Spanning Tree
A minimum-spanning-tree is a tree (without cycles) connecting all the vertices and with the smallest cost.
Comparison of Kruskal's Algorithm and Prim's Algorithm
Prim's (O(ElogV)) is more performant on dense graph. Kruskal's (O(ElogE)) is more performant on sparse graph.
Algorithm Type
Greedy
Greedy
Edge Selection
Chooses the minimum-weight edge connected to the current MST.
Sorts all edges by weight and adds them to the MST if they don't form a cycle.
Data Structures Used
Priority queue or min-heap (to efficiently select the minimum-weight edge).
Disjoint-set data structure (to check for cycles).
Complexity
O(V^2) using an adjacency matrix, O(E + V log V) using a binary heap for dense graphs.
O(E log E) to sort the edges, O(E log V) to process all edges and find MST using disjoint-set.
Suitability
More efficient for dense graphs (E is close to V^2).
Suitable for sparse graphs (E is much less than V^2).
Applications
Network design, clustering, road planning, maze generation, etc.
Network design, cluster analysis, image segmentation, etc.
Cycle Handling
Doesn't directly deal with cycles; relies on the connectedness of the graph.
Detects and avoids cycles explicitly.
Output
Yields a single MST rooted at a selected vertex.
Yields a forest of MSTs initially; they combine into a single MST as more edges are added.
Problems
1584. Min Cost to Connect All Points (Medium) Dense Graph. Prim is better.
Last updated