美文网首页
465. Optimal Account Balancing

465. Optimal Account Balancing

作者: Jeanz | 来源:发表于2018-01-10 02:12 被阅读0次

    A group of friends went on holiday and sometimes lent each other money. For example, Alice paid for Bill's lunch for $10. Then later Chris gave Alice $5 for a taxi ride. We can model each transaction as a tuple (x, y, z) which means person x gave person y $z. Assuming Alice, Bill, and Chris are person 0, 1, and 2 respectively (0, 1, 2 are the person's ID), the transactions can be represented as [[0, 1, 10], [2, 0, 5]].

    Given a list of transactions between a group of people, return the minimum number of transactions required to settle the debt.

    Note:

    1. A transaction will be given as a tuple (x, y, z). Note that x ≠ y and z > 0.
    2. Person's IDs may not be linear, e.g. we could have the persons 0, 1, 2 or we could also have the persons 0, 2, 6.

    Example 1:

    Input:
    [[0,1,10], [2,0,5]]
    
    Output:
    2
    
    Explanation:
    Person #0 gave person #1 $10.
    Person #2 gave person #0 $5.
    
    Two transactions are needed. One way to settle the debt is person #1 pays person #0 and #2 $5 each.
    

    Example 2:

    Input:
    [[0,1,10], [1,0,1], [1,2,5], [2,0,5]]
    
    Output:
    1
    
    Explanation:
    Person #0 gave person #1 $10.
    Person #1 gave person #0 $1.
    Person #1 gave person #2 $5.
    Person #2 gave person #0 $5.
    
    Therefore, person #1 only need to give person #0 $4, and all debt is settled.
    

    一刷
    题解:
    提供一系列的transaction, 问还需要几次transaction能平衡balance

    最简单的方法:backtracking
    从pos开始,如果有debts[i]与debts[pos]符号不同,那么进行交易。

    class Solution {
        // DFS
        public int minTransfers(int[][] transactions) {
            Map<Integer, Long> map = new HashMap<>();
            for(int[] t : transactions){
                long val1 = map.getOrDefault(t[0], 0L);//balance
                long val2 = map.getOrDefault(t[1], 0L);
                map.put(t[0], val1-t[2]);
                map.put(t[1], val2+t[2]);
            }
            
            List<Long> list = new ArrayList<>();
            for(long val : map.values()){
                if(val!=0) list.add(val);
            }
            Long[] debts = new Long[list.size()];
            debts = list.toArray(debts);
            return helper(debts, 0, 0);
        }
        
        int helper(Long[] debts, int pos, int count ){
            while(pos<debts.length && debts[pos] == 0) pos++;
            if(pos>=debts.length) return count;
            int res = Integer.MAX_VALUE;
            for(int i=pos+1; i<debts.length; i++){
                if((debts[pos] ^ debts[i])<0){
                    debts[i] += debts[pos];
                    res = Math.min(res, helper(debts, pos+1, count+1));
                    debts[i] -= debts[pos];//backtracking
                }
            }
            return res;
        }
    }
    

    Speed up:
    有一点greedy + backtracking的感觉,首先用sort找出-5, 5这种pair, 然后从debts list中移除。

    然后再用如上的backtracking方法

    class Solution {
        // DFS
        public int minTransfers(int[][] transactions) {
            Map<Integer, Long> map = new HashMap<>();
            for(int[] t : transactions){
                long val1 = map.getOrDefault(t[0], 0L);//balance
                long val2 = map.getOrDefault(t[1], 0L);
                map.put(t[0], val1-t[2]);
                map.put(t[1], val2+t[2]);
            }
            
            List<Long> list = new ArrayList<>();
            for(long val : map.values()){
                if(val!=0) list.add(val);
            }
            int matchCount = removeMatch(list);
            return matchCount + minTransStartFrom(list, 0);
        }
        
        private int removeMatch(List<Long> list) {
            Collections.sort(list);
            int left = 0;
            int right = list.size() - 1;
            int matchCount = 0;
            while (left < right) {
                if (list.get(left) + list.get(right) == 0) {
                    list.remove(left);
                    list.remove(right - 1);
                    right -= 2;
                    matchCount++;
                } else if (list.get(left) + list.get(right) < 0) {
                    left++;
                } else {
                    right--;
                }
            }
            return matchCount;
        }
        
         private int minTransStartFrom(List<Long> list, int start) {
            int result = Integer.MAX_VALUE;
            int n = list.size();
            while (start < n && list.get(start) == 0) {
                start++;
            }
            if (start == n) {
                return 0;
            }
            for (int i = start + 1; i < n; i++) {
                if (list.get(i) * list.get(start) < 0) {
                    list.set(i, list.get(i) + list.get(start));
                    result = Math.min(result, 1 + minTransStartFrom(list, start + 1));
                    list.set(i, list.get(i) - list.get(start));
                }
            }
            return result;
        }
    }
    

    相关文章

      网友评论

          本文标题:465. Optimal Account Balancing

          本文链接:https://www.haomeiwen.com/subject/whawnxtx.html