Update Unbounded_0_1_Knapsack.cpp

Author: yeolesanskruti

dynamic_programming/Unbounded_0_1_Knapsack.cpp

@@ -1 +1,136 @@
+/**
+ * @file
+ * @brief Implementation of the Unbounded 0/1 Knapsack Problem
+ * 
+ * @details 
+ * The Unbounded 0/1 Knapsack problem allows taking unlimited quantities of each item. 
+ * The goal is to maximize the total value without exceeding the given knapsack capacity. 
+ * Unlike the 0/1 knapsack, where each item can be taken only once, in this variation, 
+ * any item can be picked any number of times as long as the total weight stays within 
+ * the knapsack's capacity.
+ * 
+ * Given a set of N items, each with a weight and a value, represented by the arrays 
+ * `wt` and `val` respectively, and a knapsack with a weight limit W, the task is to 
+ * fill the knapsack to maximize the total value.
+ *
+ * @note weight and value of items is greater than zero.
+ *
+ * ### Algorithm
+ * The approach uses dynamic programming to build a solution iteratively. 
+ * A 2D array is used for memoization to store intermediate results, allowing 
+ * the function to avoid redundant calculations.
+ * 
+ * @author [Sanskruti Yeole](https://github.com/yeolesanskruti)
+ * @see dynamic_programming/0_1_knapsack.cpp
+ */
 
+#include <iostream>  ///< Standard input-output stream
+#include <vector>   ///< Standard library for using dynamic arrays (vectors)
+#include <cassert>  ///< For using assert function to validate test cases
+#include <cstdint>  ///< For fixed-width integer types like std::uint16_t
+
+/**
+ * @namespace dynamic_programming
+ * @brief Namespace for dynamic programming algorithms
+ */
+namespace dynamic_programming {
+
+/**
+ * @namespace Knapsack
+ * @brief Implementation of unbounded 0-1 knapsack problem
+ */
+namespace unbounded_knapsack {
+
+/**
+ * @brief Recursive function to calculate the maximum value obtainable using 
+ *        an unbounded knapsack approach.
+ *
+ * @param i Current index in the value and weight vectors.
+ * @param W Remaining capacity of the knapsack.
+ * @param val Vector of values corresponding to the items.
+ * @param wt Vector of weights corresponding to the items.
+ * @param dp 2D vector for memoization to avoid redundant calculations.
+ * @return The maximum value that can be obtained for the given index and capacity.
+ */
+int KnapSackFilling(std::uint16_t i, std::uint16_t W, 
+                    const std::vector<std::uint16_t>& val, 
+                    const std::vector<std::uint16_t>& wt, 
+                    std::vector<std::vector<int>>& dp) {
+    if (i == 0) {
+        if (wt[0] <= W) {
+            return (W / wt[0]) * val[0]; // Take as many of the first item as possible
+        } else {
+            return 0; // Can't take the first item
+        }
+    }
+    if (dp[i][W] != -1) return dp[i][W]; // Return result if available
+
+    int nottake = KnapSackFilling(i - 1, W, val, wt, dp); // Value without taking item i
+    int take = 0;
+    if (W >= wt[i]) {
+        take = val[i] + KnapSackFilling(i, W - wt[i], val, wt, dp); // Value taking item i
+    }
+    return dp[i][W] = std::max(take, nottake); // Store and return the maximum value
+}
+
+/**
+ * @brief Wrapper function to initiate the unbounded knapsack calculation.
+ *
+ * @param N Number of items.
+ * @param W Maximum weight capacity of the knapsack.
+ * @param val Vector of values corresponding to the items.
+ * @param wt Vector of weights corresponding to the items.
+ * @return The maximum value that can be obtained for the given capacity.
+ */
+int unboundedKnapsack(std::uint16_t N, std::uint16_t W, 
+                      const std::vector<std::uint16_t>& val, 
+                      const std::vector<std::uint16_t>& wt) {
+    std::vector<std::vector<int>> dp(N, std::vector<int>(W + 1, -1)); // Initialize memoization table
+    return KnapSackFilling(N - 1, W, val, wt, dp); // Start the calculation
+}
+
+/**
+ * @brief Function to run test cases for the unbounded knapsack implementation.
+ * 
+ * @details This function tests the implementation with predefined test cases.
+ * It asserts the expected outcomes to ensure correctness of the algorithm.
+ */
+void tests() {
+    // Test Case 1
+    std::uint16_t N1 = 4;  // Number of items
+    std::vector<std::uint16_t> wt1 = {1, 3, 4, 5}; // Weights of the items
+    std::vector<std::uint16_t> val1 = {6, 1, 7, 7}; // Values of the items
+    std::uint16_t W1 = 8; // Maximum capacity of the knapsack
+    // Test the function and assert the expected output
+    assert(unboundedKnapsack(N1, W1, val1, wt1) == 48);
+    std::cout << "Maximum Knapsack value " << unboundedKnapsack(N1, W1, val1, wt1) << std::endl;
+
+    // Test Case 2
+    std::uint16_t N2 = 3; // Number of items
+    std::vector<std::uint16_t> wt2 = {10, 20, 30}; // Weights of the items
+    std::vector<std::uint16_t> val2 = {60, 100, 120}; // Values of the items
+    std::uint16_t W2 = 5; // Maximum capacity of the knapsack
+    // Test the function and assert the expected output
+    assert(unboundedKnapsack(N2, W2, val2, wt2) == 0);
+    std::cout << "Maximum Knapsack value " << unboundedKnapsack(N2, W2, val2, wt2) << std::endl;
+
+    // Test Case 3
+    std::uint16_t N3 = 3; // Number of items
+    std::vector<std::uint16_t> wt3 = {2, 4, 6}; // Weights of the items
+    std::vector<std::uint16_t> val3 = {5, 11, 13};// Values of the items 
+    std::uint16_t W3 = 27;// Maximum capacity of the knapsack 
+    // Test the function and assert the expected output
+    assert(unboundedKnapsack(N3, W3, val3, wt3) == 27);
+    std::cout << "Maximum Knapsack value " << unboundedKnapsack(N3, W3, val3, wt3) << std::endl;
+  
+    std::cout << "All test cases passed!" << std::endl;
+
+}
+
+int main() {
+    tests(); // Run test cases to validate implementation
+    return 0;
+}
+
+}
+}