Add the section of unbounded knapsack problem.

codes/cpp/chapter_dynamic_programming/CMakeLists.txt

@@ -4,4 +4,6 @@ add_executable(climbing_stairs_dfs_mem climbing_stairs_dfs_mem.cpp)
 add_executable(climbing_stairs_dp climbing_stairs_dp.cpp)
 add_executable(min_cost_climbing_stairs_dp min_cost_climbing_stairs_dp.cpp)
 add_executable(min_path_sum min_path_sum.cpp)
-add_executable(knapsack knapsack.cpp)
+add_executable(unbounded_knapsack unbounded_knapsack.cpp)
+add_executable(coin_change coin_change.cpp)
+add_executable(coin_change_ii coin_change_ii.cpp)

codes/cpp/chapter_dynamic_programming/coin_change.cpp

@@ -0,0 +1,70 @@
+/**
+ * File: coin_change.cpp
+ * Created Time: 2023-07-11
+ * Author: Krahets (krahets@163.com)
+ */
+
+#include "../utils/common.hpp"
+
+/* 零钱兑换：动态规划 */
+int coinChangeDP(vector<int> &coins, int amt) {
+    int n = coins.size();
+    int MAX = amt + 1;
+    // 初始化 dp 表
+    vector<vector<int>> dp(n + 1, vector<int>(amt + 1, 0));
+    // 状态转移：首行首列
+    for (int a = 1; a <= amt; a++) {
+        dp[0][a] = MAX;
+    }
+    // 状态转移：其余行列
+    for (int i = 1; i <= n; i++) {
+        for (int a = 1; a <= amt; a++) {
+            if (coins[i - 1] > a) {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[i][a] = min(dp[i - 1][a], dp[i][a - coins[i - 1]] + 1);
+            }
+        }
+    }
+    return dp[n][amt] != MAX ? dp[n][amt] : -1;
+}
+
+/* 零钱兑换：状态压缩后的动态规划 */
+int coinChangeDPComp(vector<int> &coins, int amt) {
+    int n = coins.size();
+    int MAX = amt + 1;
+    // 初始化 dp 表
+    vector<int> dp(amt + 1, MAX);
+    dp[0] = 0;
+    // 状态转移
+    for (int i = 1; i <= n; i++) {
+        for (int a = 1; a <= amt; a++) {
+            if (coins[i - 1] > a) {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案的较小值
+                dp[a] = min(dp[a], dp[a - coins[i - 1]] + 1);
+            }
+        }
+    }
+    return dp[amt] != MAX ? dp[amt] : -1;
+}
+
+/* Driver code */
+int main() {
+    vector<int> coins = {1, 2, 5};
+    int amt = 4;
+
+    // 动态规划
+    int res = coinChangeDP(coins, amt);
+    cout << "凑到目标金额所需的最少硬币数量为 " << res << endl;
+
+    // 状态压缩后的动态规划
+    res = coinChangeDPComp(coins, amt);
+    cout << "凑到目标金额所需的最少硬币数量为 " << res << endl;
+
+    return 0;
+}

codes/cpp/chapter_dynamic_programming/coin_change_ii.cpp

@@ -0,0 +1,68 @@
+/**
+ * File: coin_change_ii.cpp
+ * Created Time: 2023-07-11
+ * Author: Krahets (krahets@163.com)
+ */
+
+#include "../utils/common.hpp"
+
+/* 零钱兑换 II：动态规划 */
+int coinChangeIIDP(vector<int> &coins, int amt) {
+    int n = coins.size();
+    // 初始化 dp 表
+    vector<vector<int>> dp(n + 1, vector<int>(amt + 1, 0));
+    // 初始化首列
+    for (int i = 0; i <= n; i++) {
+        dp[i][0] = 1;
+    }
+    // 状态转移
+    for (int i = 1; i <= n; i++) {
+        for (int a = 1; a <= amt; a++) {
+            if (coins[i - 1] > a) {
+                // 若超过背包容量，则不选硬币 i
+                dp[i][a] = dp[i - 1][a];
+            } else {
+                // 不选和选硬币 i 这两种方案之和
+                dp[i][a] = dp[i - 1][a] + dp[i][a - coins[i - 1]];
+            }
+        }
+    }
+    return dp[n][amt];
+}
+
+/* 零钱兑换 II：状态压缩后的动态规划 */
+int coinChangeIIDPComp(vector<int> &coins, int amt) {
+    int n = coins.size();
+    // 初始化 dp 表
+    vector<int> dp(amt + 1, 0);
+    dp[0] = 1;
+    // 状态转移
+    for (int i = 1; i <= n; i++) {
+        for (int a = 1; a <= amt; a++) {
+            if (coins[i - 1] > a) {
+                // 若超过背包容量，则不选硬币 i
+                dp[a] = dp[a];
+            } else {
+                // 不选和选硬币 i 这两种方案之和
+                dp[a] = dp[a] + dp[a - coins[i - 1]];
+            }
+        }
+    }
+    return dp[amt];
+}
+
+/* Driver code */
+int main() {
+    vector<int> coins = {1, 2, 5};
+    int amt = 5;
+
+    // 动态规划
+    int res = coinChangeIIDP(coins, amt);
+    cout << "凑出目标金额的硬币组合数量为 " << res << endl;
+
+    // 状态压缩后的动态规划
+    res = coinChangeIIDPComp(coins, amt);
+    cout << "凑出目标金额的硬币组合数量为 " << res << endl;
+
+    return 0;
+}

codes/cpp/chapter_dynamic_programming/unbounded_knapsack.cpp

@@ -0,0 +1,64 @@
+/**
+ * File: unbounded_knapsack.cpp
+ * Created Time: 2023-07-11
+ * Author: Krahets (krahets@163.com)
+ */
+
+#include "../utils/common.hpp"
+
+/* 完全背包：动态规划 */
+int unboundedKnapsackDP(vector<int> &wgt, vector<int> &val, int cap) {
+    int n = wgt.size();
+    // 初始化 dp 表
+    vector<vector<int>> dp(n + 1, vector<int>(cap + 1, 0));
+    // 状态转移
+    for (int i = 1; i <= n; i++) {
+        for (int c = 1; c <= cap; c++) {
+            if (wgt[i - 1] > c) {
+                // 若超过背包容量，则不选物品 i
+                dp[i][c] = dp[i - 1][c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[i][c] = max(dp[i - 1][c], dp[i][c - wgt[i - 1]] + val[i - 1]);
+            }
+        }
+    }
+    return dp[n][cap];
+}
+
+/* 完全背包：状态压缩后的动态规划 */
+int unboundedKnapsackDPComp(vector<int> &wgt, vector<int> &val, int cap) {
+    int n = wgt.size();
+    // 初始化 dp 表
+    vector<int> dp(cap + 1, 0);
+    // 状态转移
+    for (int i = 1; i <= n; i++) {
+        for (int c = 1; c <= cap; c++) {
+            if (wgt[i - 1] > c) {
+                // 若超过背包容量，则不选物品 i
+                dp[c] = dp[c];
+            } else {
+                // 不选和选物品 i 这两种方案的较大值
+                dp[c] = max(dp[c], dp[c - wgt[i - 1]] + val[i - 1]);
+            }
+        }
+    }
+    return dp[cap];
+}
+
+/* Driver code */
+int main() {
+    vector<int> wgt = {1, 2, 3};
+    vector<int> val = {5, 11, 15};
+    int cap = 4;
+
+    // 动态规划
+    int res = unboundedKnapsackDP(wgt, val, cap);
+    cout << "不超过背包容量的最大物品价值为 " << res << endl;
+
+    // 状态压缩后的动态规划
+    res = unboundedKnapsackDPComp(wgt, val, cap);
+    cout << "不超过背包容量的最大物品价值为 " << res << endl;
+
+    return 0;
+}