2022-06-12:在N*N的正方形棋盘中,有N*N个棋子,那么每个格子正好可以拥有一个棋子。 但是现在有些棋子聚集到一个格子上了,比如: 2 0 3 0 1 0 3 0 0 如上的二维数组代表,一

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2022-06-12:在NN的正方形棋盘中,有NN个棋子,那么每个格子正好可以拥有一个棋子。
但是现在有些棋子聚集到一个格子上了,比如:
2 0 3
0 1 0
3 0 0
如上的二维数组代表,一共3*3个格子,
但是有些格子有2个棋子、有些有3个、有些有1个、有些没有,
请你用棋子移动的方式,让每个格子都有一个棋子,
每个棋子可以上、下、左、右移动,每移动一步算1的代价。
返回最小的代价。
来自微软。

答案2022-06-12:

km算法,距离取负数。

代码用rust编写。代码如下:

use rand::Rng;
fn main() 
    let len: i32 = 4;
    let test_time: i32 = 1000;
    println!("测试开始");
    for _ in 0..test_time 
        let mut graph = random_valid_matrix(len);
        let ans1 = min_distance1(&mut graph);
        let ans2 = min_distance2(&mut graph);
        if ans1 != ans2 
            println!("出错了!");
            println!("ans1 = ", ans1);
            println!("ans2 = ", ans2);
            println!("===============");
        
    
    println!("测试结束");


// 暴力解
// 作为对数器
fn min_distance1(map: &mut Vec<Vec<i32>>) -> i32 
    let mut n = 0;
    let mut m = 0;
    for i in 0..map.len() as i32 
        for j in 0..map[0].len() as i32 
            n += get_max(0, map[i as usize][j as usize] - 1);
            m += if map[i as usize][j as usize] == 0 
                1
             else 
                0
            ;
        
    
    if n != m || n == 0 
        return 0;
    
    let mut nodes: Vec<Vec<i32>> = vec![];
    for i in 0..n 
        nodes.push(vec![]);
        for _ in 0..2 
            nodes[i as usize].push(0);
        
    
    let mut space: Vec<Vec<i32>> = vec![];
    for i in 0..m 
        space.push(vec![]);
        for _ in 0..2 
            space[i as usize].push(0);
        
    
    n = 0;
    m = 0;
    for i in 0..map.len() as i32 
        for j in 0..map[0].len() as i32 
            for _k in 2..map[i as usize][j as usize] 
                nodes[n as usize][0] = i;
                nodes[n as usize][1] = j;
                n += 1;
            
            if map[i as usize][j as usize] == 0 
                space[m as usize][0] = i;
                space[m as usize][1] = j;
                m += 1;
            
        
    
    return process1(&mut nodes, 0, &mut space);


fn process1(nodes: &mut Vec<Vec<i32>>, index: i32, space: &mut Vec<Vec<i32>>) -> i32 
    let mut ans = 0;
    if index == nodes.len() as i32 
        for i in 0..nodes.len() as i32 
            ans += distance(&mut nodes[i as usize], &mut space[i as usize]);
        
     else 
        ans = 2147483647;
        for i in index..nodes.len() as i32 
            swap(nodes, index, i);
            ans = get_min(ans, process1(nodes, index + 1, space));
            swap(nodes, index, i);
        
    
    return ans;


fn swap(nodes: &mut Vec<Vec<i32>>, i: i32, j: i32) 
    let tmp = nodes[i as usize].clone();
    nodes[i as usize] = nodes[j as usize].clone();
    nodes[j as usize] = tmp.clone();


fn distance(a: &mut Vec<i32>, b: &mut Vec<i32>) -> i32 
    return abs(a[0] - b[0]) + abs(a[1] - b[1]);

fn abs(a: i32) -> i32 
    if a < 0 
        -a
     else 
        a
    


// 正式方法
// KM算法
fn min_distance2(map: &mut Vec<Vec<i32>>) -> i32 
    let mut n = 0;
    let mut m = 0;
    for i in 0..map.len() as i32 
        for j in 0..map[0].len() as i32 
            n += get_max(0, map[i as usize][j as usize] - 1);
            m += if map[i as usize][j as usize] == 0 
                1
             else 
                0
            ;
        
    
    if n != m || n == 0 
        return 0;
    
    let mut nodes: Vec<Vec<i32>> = vec![];
    for i in 0..n 
        nodes.push(vec![]);
        for _ in 0..2 
            nodes[i as usize].push(0);
        
    
    let mut space: Vec<Vec<i32>> = vec![];
    for i in 0..m 
        space.push(vec![]);
        for _ in 0..2 
            space[i as usize].push(0);
        
    
    n = 0;
    m = 0;
    for i in 0..map.len() as i32 
        for j in 0..map[0].len() as i32 
            for _k in 2..=map[i as usize][j as usize] 
                nodes[n as usize][0] = i;
                nodes[n as usize][1] = j;
                n += 1;
            
            if map[i as usize][j as usize] == 0 
                space[m as usize][0] = i;
                space[m as usize][1] = j;
                m += 1;
            
        
    
    let mut graph: Vec<Vec<i32>> = vec![];
    for i in 0..n 
        graph.push(vec![]);
        for _ in 0..n 
            graph[i as usize].push(0);
        
    
    for i in 0..n 
        for j in 0..n 
            graph[i as usize][j as usize] =
                -distance(&mut nodes[i as usize], &mut space[j as usize]);
        
    
    return -km(&mut graph);


fn get_max<T: Clone + Copy + std::cmp::PartialOrd>(a: T, b: T) -> T 
    if a > b 
        a
     else 
        b
    


fn get_min<T: Clone + Copy + std::cmp::PartialOrd>(a: T, b: T) -> T 
    if a < b 
        a
     else 
        b
    


fn km(graph: &mut Vec<Vec<i32>>) -> i32 
    let nn = graph.len() as i32;
    let mut match0: Vec<i32> = vec![];
    let mut lx: Vec<i32> = vec![];
    let mut ly: Vec<i32> = vec![];
    // dfs过程中,碰过的点!
    let mut x: Vec<bool> = vec![];
    let mut y: Vec<bool> = vec![];
    // 降低的预期!
    // 公主上,打一个,降低预期的值,只维持最小!
    let mut slack: Vec<i32> = vec![];
    let mut falsev: Vec<bool> = vec![];
    for _ in 0..nn 
        match0.push(0);
        lx.push(0);
        ly.push(0);
        x.push(false);
        y.push(false);
        slack.push(0);
        falsev.push(false);
    
    let invalid = 2147483647;
    for i in 0..nn 
        match0[i as usize] = -1;
        lx[i as usize] = -invalid;
        for j in 0..nn 
            lx[i as usize] = get_max(lx[i as usize], graph[i as usize][j as usize]);
        
        ly[i as usize] = 0;
    
    for from in 0..nn 
        for i in 0..nn 
            slack[i as usize] = invalid;
        
        x = falsev.clone();
        y = falsev.clone();
        // dfs() : from王子,能不能不降预期,匹配成功!
        // 能:dfs返回true!
        // 不能:dfs返回false!
        while !dfs(
            from,
            &mut x,
            &mut y,
            &mut lx,
            &mut ly,
            &mut match0,
            &mut slack,
            graph,
        ) 
            // 刚才的dfs,失败了!
            // 需要拿到,公主的slack里面,预期下降幅度的最小值!
            let mut d = invalid;
            for i in 0..nn 
                if !y[i as usize] && slack[i as usize] < d 
                    d = slack[i as usize];
                
            
            // 按照最小预期来调整预期
            for i in 0..nn 
                if x[i as usize] 
                    lx[i as usize] = lx[i as usize] - d;
                
                if y[i as usize] 
                    ly[i as usize] = ly[i as usize] + d;
                
            
            x = falsev.clone();
            y = falsev.clone();
            // 然后回到while里,再次尝试
        
    
    let mut ans = 0;
    for i in 0..nn 
        ans += lx[i as usize] + ly[i as usize];
    
    return ans;


// from, 当前的王子
// x,王子碰没碰过
// y, 公主碰没碰过
// lx,所有王子的预期
// ly, 所有公主的预期
// match,所有公主,之前的分配,之前的爷们!
// slack,连过,但没允许的公主,最小下降的幅度
// map,报价,所有王子对公主的报价
// 返回,from号王子,不降预期能不能配成!
fn dfs(
    from: i32,
    x: &mut V

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