A typescript implementation of the bellman-ford algorithm.
The following definition is quoted from Wikipedia
(https://en.wikipedia.org/wiki/Bellman%E2%80%93Ford_algorithm):
The Bellman–Ford algorithm is an algorithm that computes shortest paths from a single source
vertex to all of the other vertices in a weighted digraph. It is slower than Dijkstra's algorithm
for the same problem, but more versatile, as it is capable of handling graphs in which some of the
edge weights are negative numbers. The algorithm was first proposed by Alfonso Shimbel (1955), but
is instead named after Richard Bellman and Lester Ford Jr., who published it in 1958 and 1956,
respectively. Edward F. Moore also published a variation of the algorithm in 1959, and for this
reason it is also sometimes called the Bellman–Ford–Moore algorithm.
Install
Usage
-
Simple
import type { IBellmanFordGraph } from '@algorithm.ts/bellman-ford'
import bellmanFord from '@algorithm.ts/bellman-ford'
const graph: IBellmanFordGraph<number> = {
N: 4,
source: 0,
edges: [
{ to: 1, cost: 2 },
{ to: 2, cost: 2 },
{ to: 3, cost: 2 },
{ to: 3, cost: 1 },
],
G: [[0], [1, 2], [3], []],
}
const result = bellmanFord(graph)
-
Options
| Name | Type | Required | Description |
| :---: | :-----: | :------: | :---------- | ------------------------------------------------ |
| INF
| number | bigint
| false
| A big number, representing the unreachable cost. |
Example
-
Get shortest path.
import type { IBellmanFordGraph } from '@algorithm.ts/bellman-ford'
import bellmanFord from '@algorithm.ts/bellman-ford'
import { getShortestPath } from '@algorithm.ts/graph'
const A = 0
const B = 1
const C = 2
const D = 3
const graph: IBellmanFordGraph<number> = {
N: 4,
source: A,
edges: [
{ to: B, cost: 1 },
{ to: A, cost: -1 },
{ to: C, cost: 0.87 },
{ to: B, cost: -0.87 },
{ to: D, cost: 5 },
{ to: C, cost: -5 },
],
G: [[0], [1, 2], [3, 4], [5]],
}
const result = _bellmanFord.bellmanFord(graph)
assert(result.negativeCycle === false)
getShortestPath(result.bestFrom, Nodes.A, Nodes.A)
getShortestPath(result.bestFrom, Nodes.A, Nodes.B)
getShortestPath(result.bestFrom, Nodes.A, Nodes.C)
getShortestPath(result.bestFrom, Nodes.A, Nodes.D)
-
A solution for leetcode "Number of Ways to Arrive at Destination"
(https://leetcode.com/problems/number-of-ways-to-arrive-at-destination/):
import type { IBellmanFordEdge, IBellmanFordGraph } from '@algorithm.ts/bellman-ford'
import { bellmanFord } from '@algorithm.ts/bellman-ford'
const MOD = 1e9 + 7
export function countPaths(N: number, roads: number[][]): number {
const edges: Array<IBellmanFordEdge<number>> = []
const G: number[][] = new Array(N)
for (let i = 0; i < N; ++i) G[i] = []
for (const [from, to, cost] of roads) {
G[from].push(edges.length)
edges.push({ to, cost })
G[to].push(edges.length)
edges.push({ to: from, cost })
}
const source = 0
const target = N - 1
const graph: IBellmanFordGraph<number> = { N, source: target, edges, G }
const result = bellmanFord(graph, { INF: 1e12 })
if (result.hasNegativeCycle) return -1
const { dist } = result
const dp: number[] = new Array(N).fill(-1)
return dfs(source)
function dfs(o: number): number {
if (o === target) return 1
let answer = dp[o]
if (answer !== -1) return answer
answer = 0
const d = dist[o]
for (const idx of G[o]) {
const e: IBellmanFordEdge<number> = edges[idx]
if (dist[e.to] + e.cost === d) {
const t = dfs(e.to)
answer = modAdd(answer, t)
}
}
return dp[o] = answer
}
}
function modAdd(x: number, y: number): number {
const z: number = x + y
return z < MOD ? z : z - MOD
}
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