Add the chapter of greedy. (#633)

Add the section of fractional knapsack.
This commit is contained in:
Yudong Jin
2023-07-20 18:26:54 +08:00
committed by GitHub
parent c54536d1a1
commit 2b7d7aa827
20 changed files with 633 additions and 4 deletions

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/**
* File: coin_change_greedy.java
* Created Time: 2023-07-20
* Author: Krahets (krahets@163.com)
*/
package chapter_greedy;
import java.util.Arrays;
public class coin_change_greedy {
/* 零钱兑换:贪心 */
static int coinChangeGreedy(int[] coins, int amt) {
// 假设 coins 列表有序
int i = coins.length - 1;
int count = 0;
// 循环进行贪心选择,直到无剩余金额
while (amt > 0) {
// 找到小于且最接近剩余金额的硬币
while (coins[i] > amt) {
i--;
}
// 选择 coins[i]
amt -= coins[i];
count++;
}
// 若未找到可行方案,则返回 -1
return amt == 0 ? count : -1;
}
public static void main(String[] args) {
// 贪心:能够保证找到全局最优解
int[] coins = { 1, 5, 10, 20, 50, 100 };
int amt = 186;
int res = coinChangeGreedy(coins, amt);
System.out.println("\ncoins = " + Arrays.toString(coins) + ", amt = " + amt);
System.out.println("凑到 " + amt + " 所需的最少硬币数量为 " + res);
// 贪心:无法保证找到全局最优解
coins = new int[] { 1, 20, 50 };
amt = 60;
res = coinChangeGreedy(coins, amt);
System.out.println("\ncoins = " + Arrays.toString(coins) + ", amt = " + amt);
System.out.println("凑到 " + amt + " 所需的最少硬币数量为 " + res);
System.out.println("实际上需要的最少数量为 3 ,即 20 + 20 + 20");
// 贪心:无法保证找到全局最优解
coins = new int[] { 1, 49, 50 };
amt = 98;
res = coinChangeGreedy(coins, amt);
System.out.println("\ncoins = " + Arrays.toString(coins) + ", amt = " + amt);
System.out.println("凑到 " + amt + " 所需的最少硬币数量为 " + res);
System.out.println("实际上需要的最少数量为 2 ,即 49 + 49");
}
}

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/**
* File: fractional_knapsack.java
* Created Time: 2023-07-20
* Author: Krahets (krahets@163.com)
*/
package chapter_greedy;
import java.util.Arrays;
import java.util.Comparator;
/* 物品 */
class Item {
int w; // 物品重量
int v; // 物品价值
public Item(int w, int v) {
this.w = w;
this.v = v;
}
}
public class fractional_knapsack {
/* 分数背包:贪心 */
static double fractionalKnapsack(int[] wgt, int[] val, int cap) {
// 创建物品列表,包含两个属性:重量、价值
Item[] items = new Item[wgt.length];
for (int i = 0; i < wgt.length; i++) {
items[i] = new Item(wgt[i], val[i]);
}
// 按照单位价值 item.v / item.w 从高到低进行排序
Arrays.sort(items, Comparator.comparingDouble(item -> -((double) item.v / item.w)));
// 循环贪心选择
double res = 0;
for (Item item : items) {
if (item.w <= cap) {
// 若剩余容量充足,则将当前物品整个装进背包
res += item.v;
cap -= item.w;
} else {
// 若剩余容量不足,则将当前物品的一部分装进背包
res += (double) item.v / item.w * cap;
// 已无剩余容量,因此跳出循环
break;
}
}
return res;
}
public static void main(String[] args) {
int[] wgt = { 10, 20, 30, 40, 50 };
int[] val = { 50, 120, 150, 210, 240 };
int cap = 50;
// 贪心算法
double res = fractionalKnapsack(wgt, val, cap);
System.out.println("不超过背包容量的最大物品价值为 " + res);
}
}