【潜意识Java】深度解析黑马项目《苍穹外卖》与蓝桥杯算法的结合问题

import java.util.Arrays;
public class TSP {
    // 定义无穷大
    static final int INF = Integer.MAX_VALUE;
    // 计算最短路径
    public static int solveTSP(int[][] dist) {
        int n = dist.length;
        // dp[i][j]表示访问完i个城市后，当前城市为j的最小路径长度
        int[][] dp = new int[1 << n][n];
        
        // 初始化dp数组
        for (int i = 0; i < (1 << n); i++) {
            Arrays.fill(dp[i], INF);
        }
        dp[1][0] = 0;  // 起点为0，已经访问了第0个城市
        
        // 动态规划状态转移
        for (int mask = 1; mask < (1 << n); mask++) {
            for (int u = 0; u < n; u++) {
                if ((mask & (1 << u)) == 0) continue;  // 如果u没有被访问过，跳过
                for (int v = 0; v < n; v++) {
                    if ((mask & (1 << v)) > 0) continue;  // 如果v已经访问过，跳过
                    dp[mask | (1 << v)][v] = Math.min(dp[mask | (1 << v)][v], dp[mask][u] + dist[u][v]);
                }
            }
        }
        // 返回最终的最短路径长度
        int ans = INF;
        for (int i = 1; i < n; i++) {
            ans = Math.min(ans, dp[(1 << n) - 1][i] + dist[i][0]);
        }
        return ans;
    }
    public static void main(String[] args) {
        // 假设有5个配送点，存储配送点之间的距离
        int[][] dist = {
            {0, 10, 15, 20, 25},
            {10, 0, 35, 25, 30},
            {15, 35, 0, 30, 5},
            {20, 25, 30, 0, 20},
            {25, 30, 5, 20, 0}
        };
        int result = solveTSP(dist);
        System.out.println("最短配送路径长度为: " + result);
    }
}

import java.util.*;
class Product {
    String name;
    int rating;
    int sales;
    public Product(String name, int rating, int sales) {
        this.name = name;
        this.rating = rating;
        this.sales = sales;
    }
}
public class ProductRecommendation {
    public static List<Product> recommendProducts(List<Product> products) {
        // 按照评分和销量的加权和进行排序，评分更高、销量更大的商品排在前面
        products.sort((p1, p2) -> {
            double score1 = p1.rating * 0.7 + p1.sales * 0.3;
            double score2 = p2.rating * 0.7 + p2.sales * 0.3;
            return Double.compare(score2, score1);  // 降序排序
        });
        return products;
    }
    public static void main(String[] args) {
        List<Product> products = Arrays.asList(
            new Product("商品A", 4, 500),
            new Product("商品B", 5, 300),
            new Product("商品C", 3, 700),
            new Product("商品D", 4, 800)
        );
        List<Product> recommended = recommendProducts(products);
        System.out.println("推荐商品:");
        for (Product p : recommended) {
            System.out.println(p.name + " - 评分: " + p.rating + " 销量: " + p.sales);
        }
    }
}