Problem 37

问题描述:

The number 3797 has an interesting property. Being prime itself, it is possible to continuously remove digits from left to right, and remain prime at each stage: 3797, 797, 97, and 7. Similarly we can work from right to left: 3797, 379, 37, and 3.

Find the sum of the only eleven primes that are both truncatable from left to right and right to left.

NOTE: 2, 3, 5, and 7 are not considered to be truncatable primes.

 

 

解决问题:

package projecteuler;

import java.util.Arrays;

public class Problem37 {

	public static boolean prime[] ;
	public static int UP = 11;
	
	public static boolean IsPrime(int number) {
		boolean result = true;

		if(number==1||number==2){
			return true;
		} else if (number % 2 == 0) {
			return true;
		} else {
			int middle = (int) Math.sqrt(number);
			for (int i = 3; i <= middle; i += 2) {
				if (number % i == 0) {
					return false;
				}
			}
		}
		return true;
	}

	public static boolean IsNumber(int number){
		
		int tmp = number;
		int max = 10;
		int n;
		do{
			n = tmp%max;
//			System.out.println("1:"+tmp%max);
			if(!prime[n]){
				return false;
			}
			max = max*10;
		}while(n!=number);
		max = max/100;
//		System.out.println("Max:"+max);
		do{
			n = tmp/max;
//			System.out.println("2:"+tmp/max);
			if(!prime[n]){
				return false;
			}
			max = max/10;;
		}while(n!=number);
		return true;

	}
	
	public static void main(String[] args){
		long t1 = System.currentTimeMillis();
		prime = new boolean[3000000];
		Arrays.fill(prime, false);
		for (int i = 3; i < 3000000; i=i+2) {
			if(IsPrime(i))
				prime[i] = true;
		}
		prime[2] = true;
		int n = 11;
		int count = 0;
		int sum = 0;
		do{
			if(IsNumber(n)){
				sum +=n;
				count++;
				System.out.println(n);
			}
			n = n+2;
		}while(count<UP);
		long t2 = System.currentTimeMillis();
		System.out.println("Sum:"+sum);
		
		System.out.println(t2-t1);
	}
}

 

 

 

### LeetCode Problem 37: Sudoku Solver #### Problem Description The task involves solving a partially filled Sudoku puzzle. The input is represented as a two-dimensional integer array `board` where each element can be either a digit from '1' to '9' or '.' indicating empty cells. #### Solution Approach To solve this problem, one approach uses backtracking combined with depth-first search (DFS). This method tries placing numbers between 1 and 9 into every cell that contains '.', checking whether it leads to a valid solution by ensuring no conflicts arise within rows, columns, and subgrids[^6]. ```cpp void solveSudoku(vector<vector<char>>& board) { backtrack(board); } bool backtrack(vector<vector<char>> &board){ for(int row = 0; row < 9; ++row){ for(int col = 0; col < 9; ++col){ if(board[row][col] != '.') continue; for(char num='1';num<='9';++num){ if(isValidPlacement(board,row,col,num)){ placeNumber(num,board,row,col); if(backtrack(board)) return true; removeNumber(num,board,row,col); } } return false; } } return true; } ``` In the provided code snippet: - A function named `solveSudoku()` initiates the process. - Within `backtrack()`, nested loops iterate over all positions in the grid looking for unassigned spots denoted by '.' - For any such spot found, attempts are made to insert digits ranging from '1' through '9'. - Before insertion, validation checks (`isValidPlacement`) ensure compliance with Sudoku rules regarding uniqueness per row/column/subgrid constraints. - If inserting a number results in reaching a dead end without finding a complete solution, removal occurs before trying another possibility. This algorithm continues until filling out the entire board correctly or exhausting possibilities when returning failure status upward along recursive calls stack frames. --related questions-- 1. How does constraint propagation improve efficiency while solving puzzles like Sudoku? 2. Can genetic algorithms provide alternative methods for tackling similar combinatorial problems effectively? 3. What optimizations could enhance performance further beyond basic DFS/backtracking techniques used here?
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