【自学记录】【23.11.02】正则表达式

背包问题

0-1背包问题解决方式(二维数组)

0-1背包示例代码

    public static void func1(int[] weight, int[] value, int bagSize){

        //初始化dp数组
        int goods = weight.length;
        int[][] dp = new  int[goods][bagSize+1];
        for (int i = weight[0]; i <=bagSize; i++) {
            dp[0][i] = value[0];
        }
        for(int i = 1;i<goods;i++){
            for (int j = 1; j <= bagSize; j++) {
                if(j<weight[i]){
                    dp[i][j] = dp[i-1][j];
                }else{
                    dp[i][j] = Math.max(dp[i-1][j],value[i]+dp[i-1][j-weight[i]]);
                }
            }
        }
        for (int i = 0; i < goods; i++) {
            for (int j = 0; j <=bagSize; j++) {
                System.out.print(dp[i][j]+" ");
            }
            System.out.println();
        }




    }












//main方法中代码
        int[] value = {15,20,30};
        int[] weight = {1,3,4};
        int bagSize = 4;
        func1(weight,value,bagSize);

0-1背包问题解决方式(一维数组)

示例代码 

   public static void func2(int[] weight, int[] value, int bagWeight) {
        int wLen = weight.length;
        //定义dp数组：dp[j]表示背包容量为j时，能获得的最大价值
        int[] dp = new int[bagWeight + 1];
        //遍历顺序：先遍历物品，再遍历背包容量
        for (int i = 0; i < wLen; i++) {
            for (int j = bagWeight; j >= weight[i]; j--) {
                dp[j] = Math.max(dp[j], dp[j - weight[i]] + value[i]);
            }
        }
        //打印dp数组
        for (int j = 0; j <= bagWeight; j++) {
            System.out.print(dp[j] + " ");
        }
    }
}

LeetCode T416 等和子集问题

题目链接:416. 分割等和子集 - 力扣（LeetCode）

题目思路:

题目代码:

class Solution {
    public boolean canPartition(int[] nums) {
        if(nums.length == 1){
            return false;
        }
        int sum = 0;
        for(int i:nums){
            sum += i;
        }
        if(sum % 2 == 1){
            return false;
        }
        int bagSize = sum/2;
        int[] dp = new int[bagSize+1];
        //初始化均为0
        for(int i = 0;i<nums.length;i++){
            for(int j = bagSize;j>=nums[i];j--){
                dp[j] = Math.max(dp[j],dp[j-nums[i]]+nums[i]);
            }
        }
        if(dp[bagSize] == bagSize){
            return true;
        }
       return false;

    }
}