- ✕この概要は、複数のオンライン ソースに基づいて AI を使用して生成されました。元のソース情報を表示するには、[詳細情報] リンクを使用します。
The Bellman-Ford algorithm is a single-source shortest path algorithm that works on weighted graphs, including those with negative edge weights. Unlike Dijkstra’s algorithm, it can detect negative weight cycles and report them.
It works on the principle of relaxation, where distances are iteratively updated until the shortest paths are found or a negative cycle is detected.
Pseudocode:
def bellman_ford(vertices, edges, source):# Step 1: Initialize distancesdist = [float("inf")] * verticesprev = [None] * verticesdist[source] = 0# Step 2: Relax edges |V| - 1 timesfor _ in range(vertices - 1):for u, v, w in edges:if dist[u] != float("inf") and dist[u] + w < dist[v]:dist[v] = dist[u] + wprev[v] = u# Step 3: Check for negative weight cyclesfor u, v, w in edges:if dist[u] != float("inf") and dist[u] + w < dist[v]:print("Graph contains a negative weight cycle")return None, Nonereturn dist, prevコピーしました。✕コピーHow it works:
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When the algorithm is used to find shortest paths, the existence of negative cycles is a problem, preventing the algorithm from finding a correct answer. However, since it terminates upon finding a negative cycle, the Bellman–Ford algorithm can be used for applications in which this is the target to be sought – for example in cycle-cancelling techniques in network flow analysis.
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2024年9月21日 · Learn the Bellman-Ford Algorithm with an example, time complexity analysis, and code implementation for efficient shortest path finding in this tutorial.
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2025年7月21日 · Learn how to implement the Bellman Ford algorithm in Python, C++, and Java with complete code examples and handle negative edge weights …
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