廣度優先算法(Breadth-First Search),同廣度優先搜索,又稱做寬度優先搜索,或橫向優先搜索,簡稱BFS,是一種圖形搜索演算法。簡單的說,BFS是從根節點開始,沿着樹的寬度遍歷樹的節點,若是發現目標,則演算終止。廣度優先搜索的實現通常採用open-closed表。git
有這麼一個迷宮:github
6 5 0 1 0 0 0 0 0 0 1 0 0 1 0 1 0 1 1 1 0 0 0 1 0 0 1 0 1 0 0 0
其中第一行6表明行數,5表明列表,0表明能夠走的路線。1表明牆壁。
假想有一個x軸和y軸, 開始位置: 0,0 終點位置: 6,5
用程序實現最短的路線以下:golang
package main import ( "fmt" "os" ) func readMaze(filename string) [][]int { file, err := os.Open(filename) if err != nil { panic(err) } var row, col int fmt.Fscanf(file, "%d %d", &row, &col) maze := make([][]int, row) for i := range maze { maze[i] = make([]int, col) for j := range maze[i] { fmt.Fscanf(file, "%d", &maze[i][j]) } } return maze } type point struct { i, j int } var dirs = [4]point{ {-1, 0},{0, -1},{1, 0},{0, 1}, } func (p point) add(r point) point { return point{p.i + r.i, p.j + r.j } } func (p point) at(grid [][]int) (int, bool) { if p.i < 0 || p.i >= len(grid) { return 0, false } if p.j < 0 || p.j >= len(grid[p.i]) { return 0, false } return grid[p.i][p.j], true } func walk(maze [][]int, start, end point) [][]int { steps := make([][]int, len(maze)) for i := range steps { steps[i] = make([]int, len(maze[i])) } Q := []point{start} for len(Q) > 0 { cur := Q[0] Q = Q[1:] if cur == end { break } for _, dir := range dirs { next := cur.add(dir) val, ok := next.at(maze) if !ok || val == 1 { continue } val, ok = next.at(steps) if !ok || val != 0 { continue } if next == start { continue } curSteps, _ := cur.at(steps) steps[next.i][next.j] = curSteps + 1 Q = append(Q, next) } } return steps } func main() { maze := readMaze("./maze.in") for i := range maze { for _, j := range maze[i] { fmt.Printf("%3d", j) } fmt.Println() } fmt.Println() steps := walk(maze, point{0,0},point{len(maze) - 1, len(maze[0]) - 1}) for _, row := range steps { for _, val := range row { fmt.Printf("%3d", val) } fmt.Println() } }
golang數據結構:
https://github.com/Workiva/go-datastructures
https://github.com/emirpasic/gods算法