Added Floyd–Warshall algorithm in comparison table.

gazeldx · gazeldx · commit 8c0c7921043c · 2025-02-13T21:23:00.000+08:00
diff --git a/en/1-1000/743-network-delay-time.md b/en/1-1000/743-network-delay-time.md
@@ -54,12 +54,13 @@ The following code will introduce how to optimize.
 For a detailed description of **Dijkstra's algorithm**, please refer to [1514. Path with Maximum Probability](../1001-2000/1514-path-with-maximum-probability.md).
 
 ### Common graph theory algorithm comparison table
-|Algorithm name|Main application scenarios|Optimization methods|Importance|Difficulty|min_distances|Negative weights|Additional application scenarios|
+|Algorithm name|Main application scenarios|Optimization methods|Importance|Difficulty|min_<br>distances|Negative weights|Additional application scenarios|
 |--------------|--------------------------|--------------------|----------|----------|-------------|----------------|--------------------------------|
-|[Prim's algorithm](../1001-2000/1584-min-cost-to-connect-all-points.md)     |Minimum Spanning Tree       |Heap Sort Simplify|Important     |Medium         |Used    |Can handle||
-|[Kruskal's algorithm](../1001-2000/1584-min-cost-to-connect-all-points-2.md)|Minimum Spanning Tree       |No need           |important     |Relatively hard|Not used|Can handle|Relative: [Undirected Graph Cycle Detection](./684-redundant-connection.md), [Directed Graph Cycle Detection](./685-redundant-connection-ii.md)|
-|[Dijkstra's algorithm](../1001-2000/1514-path-with-maximum-probability.md)  |Single-Source Shortest Path |Heap Sort         |Very important|Relatively hard|Used    |Cannot handle||
-|[Bellman-Ford algorithm](./743-network-delay-time.md)                       |Single-Source Shortest Path |Queue-Improved    |Very Important|Easy           |Used    |Can handle|[Detect Negative Cycles](https://www.geeksforgeeks.org/detect-negative-cycle-graph-bellman-ford/), <br>[Shortest Hop-Bounded Paths](./787-cheapest-flights-within-k-stops.md)|
+|[Prim's algorithm](../1001-2000/1584-min-cost-to-connect-all-points.md)                                                     |Minimum Spanning Tree       |Heap Sort Simplify|Important     |Medium         |Used    |Can handle||
+|[Kruskal's algorithm](../1001-2000/1584-min-cost-to-connect-all-points-2.md)                                                |Minimum Spanning Tree       |No need           |important     |Relatively hard|Not used|Can handle|Relative: [Undirected Graph Cycle Detection](./684-redundant-connection.md), [Directed Graph Cycle Detection](./685-redundant-connection-ii.md)|
+|[Dijkstra's algorithm](../1001-2000/1514-path-with-maximum-probability.md)                                                  |Single-Source Shortest Path |Heap Sort         |Very important|Relatively hard|Used    |Cannot handle||
+|[Bellman-Ford algorithm](./743-network-delay-time.md)                                                                       |Single-Source Shortest Path |Queue-Improved    |Very Important|Easy           |Used    |Can handle|[Detect Negative Cycles](https://www.geeksforgeeks.org/detect-negative-cycle-graph-bellman-ford/), <br>[Shortest Hop-Bounded Paths](./787-cheapest-flights-within-k-stops.md)|
+|[Floyd–Warshall](../1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md)|Multi-Source Shortest Path  |No need           |Less important|Relatively hard|Used    |Can handle||
 
 ## Complexity
 **V**: vertex count, **E**: Edge count.
diff --git a/en/1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md b/en/1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md
@@ -65,9 +65,11 @@ The city 0 has 1 neighboring city at a distanceThreshold = 2.
 </details>
 
 ## Intuition
-Just like the `Hints` says, you can use **Floyd-Warshall algorithm** to compute any-point to any-point shortest distances.
+Just like the `Hints` says, you can use **Floyd-Warshall Algorithm** to compute any-point to any-point shortest distances.
 
-Or you can also do **Dijkstra algorithm** from every node due to the weights are non-negative.
+Or you can also do **Dijkstra Algorithm** from every node due to the weights are non-negative.
+
+Or you can also do **Queue-Improved Bellman-Ford Algorithm** from every node.
 
 ## Complexity
 * Time: `O(N^3)`.
diff --git a/zh/1-1000/743-network-delay-time.md b/zh/1-1000/743-network-delay-time.md
@@ -58,10 +58,11 @@
 
 |算法名称|主要的适用场景|优化方式|重要度|难度|min_<br>distances|负边权值|额外的适用场景|
 |-------|-----------|-------|-------|---|-------------|--------|------------|
-|[Prim算法](../1001-2000/1584-min-cost-to-connect-all-points.md)     |最小生成树  |堆排序简化       |重要   |中等|用到|能处理||
-|[Kruskal算法](../1001-2000/1584-min-cost-to-connect-all-points-2.md)|最小生成树  |无需优化         |重要   |较难|不用|能处理|相关：[无向图环检测](./684-redundant-connection.md), [有向图环检测](./685-redundant-connection-ii.md)|
-|[Dijkstra算法](../1001-2000/1514-path-with-maximum-probability.md)  |单源最短路径|堆排序优化       |很重要|较难|用到|不能处理||
-|[Bellman-Ford算法](./743-network-delay-time.md)                     |单源最短路径|集合优化|很重要|简单|用到|能处理|[负环检测](https://www.geeksforgeeks.org/detect-negative-cycle-graph-bellman-ford/), [限定步数最短路径](./787-cheapest-flights-within-k-stops.md)|
+|[Prim算法](../1001-2000/1584-min-cost-to-connect-all-points.md)                                                       |最小生成树  |堆排序简化|重要   |中等|用到|能处理||
+|[Kruskal算法](../1001-2000/1584-min-cost-to-connect-all-points-2.md)                                                  |最小生成树  |无需优化  |重要   |较难|不用|能处理|相关：[无向图环检测](./684-redundant-connection.md), [有向图环检测](./685-redundant-connection-ii.md)|
+|[Dijkstra算法](../1001-2000/1514-path-with-maximum-probability.md)                                                    |单源最短路径|堆排序优化 |很重要 |较难|用到|无能力||
+|[Bellman-Ford](./743-network-delay-time.md)                                                                       |单源最短路径|集合优化  |很重要  |简单|用到|能处理|[负环检测](https://www.geeksforgeeks.org/detect-negative-cycle-graph-bellman-ford/), [限定步数最短路径](./787-cheapest-flights-within-k-stops.md)|
+|[Floyd–Warshall](../1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md)|多源最短路径|无需优化  |较不重要|较难|用到|能处理||
 
 ## 复杂度
 **V**: 顶点数量，**E**: 边的数量。
diff --git a/zh/1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md b/zh/1001-2000/1334-find-the-city-with-the-smallest-number-of-neighbors-at-a-threshold-distance.md
@@ -69,6 +69,8 @@
 
 或者，你可以多次调用 **Dijkstra 算法**，每次调用时用不同的城市做为`起始城市`。
 
+或者，你可以多次调用 **集合优化的 Bellman-Ford 算法**，每次调用时用不同的城市做为`起始城市`。
+
 ## Complexity
 * Time: `O(N^3)`.
 * Space: `O(N^2)`.
