diff --git a/DIRECTORY.md b/DIRECTORY.md index fc52f313c3f1..70de110e86ea 100644 --- a/DIRECTORY.md +++ b/DIRECTORY.md @@ -783,6 +783,7 @@ * [StrassenMatrixMultiplicationTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/divideandconquer/StrassenMatrixMultiplicationTest.java) * dynamicprogramming * [BoardPathTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/dynamicprogramming/BoardPathTest.java) + * [BruteForceKnapsackTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsackTest.java) * [CatalanNumberTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/dynamicprogramming/CatalanNumberTest.java) * [ClimbStairsTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/dynamicprogramming/ClimbStairsTest.java) * [CountFriendsPairingTest](https://github.com/TheAlgorithms/Java/blob/master/src/test/java/com/thealgorithms/dynamicprogramming/CountFriendsPairingTest.java) diff --git a/src/main/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsack.java b/src/main/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsack.java index b433c44b9077..3c1851a8c46c 100644 --- a/src/main/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsack.java +++ b/src/main/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsack.java @@ -1,39 +1,67 @@ package com.thealgorithms.dynamicprogramming; -/* A Naive recursive implementation -of 0-1 Knapsack problem */ +/** + * A naive recursive implementation of the 0-1 Knapsack problem. + * + *

The 0-1 Knapsack problem is a classic optimization problem where you are + * given a set of items, each with a weight and a value, and a knapsack with a + * fixed capacity. The goal is to determine the maximum value that can be + * obtained by selecting a subset of the items such that the total weight does + * not exceed the knapsack's capacity. Each item can either be included (1) or + * excluded (0), hence the name "0-1" Knapsack.

+ * + *

This class provides a brute-force recursive approach to solving the + * problem. It evaluates all possible combinations of items to find the optimal + * solution, but this approach has exponential time complexity and is not + * suitable for large input sizes.

+ * + *

Time Complexity: O(2^n), where n is the number of items.

+ * + *

Space Complexity: O(n), due to the recursive function call stack.

+ */ public final class BruteForceKnapsack { private BruteForceKnapsack() { } - // Returns the maximum value that - // can be put in a knapsack of - // capacity W + + /** + * Solves the 0-1 Knapsack problem using a recursive brute-force approach. + * + * @param w the total capacity of the knapsack + * @param wt an array where wt[i] represents the weight of the i-th item + * @param val an array where val[i] represents the value of the i-th item + * @param n the number of items available for selection + * @return the maximum value that can be obtained with the given capacity + * + *

The function uses recursion to explore all possible subsets of items. + * For each item, it has two choices: either include it in the knapsack + * (if it fits) or exclude it. It returns the maximum value obtainable + * through these two choices.

+ * + *

Base Cases: + *

+ * + *

Recursive Steps: + *

+ */ static int knapSack(int w, int[] wt, int[] val, int n) { - // Base Case if (n == 0 || w == 0) { return 0; } - // If weight of the nth item is - // more than Knapsack capacity W, - // then this item cannot be included - // in the optimal solution if (wt[n - 1] > w) { return knapSack(w, wt, val, n - 1); - } // Return the maximum of two cases: - // (1) nth item included - // (2) not included - else { - return Math.max(val[n - 1] + knapSack(w - wt[n - 1], wt, val, n - 1), knapSack(w, wt, val, n - 1)); + } else { + return Math.max(knapSack(w, wt, val, n - 1), val[n - 1] + knapSack(w - wt[n - 1], wt, val, n - 1)); } } - - // Driver code - public static void main(String[] args) { - int[] val = new int[] {60, 100, 120}; - int[] wt = new int[] {10, 20, 30}; - int w = 50; - int n = val.length; - System.out.println(knapSack(w, wt, val, n)); - } } diff --git a/src/test/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsackTest.java b/src/test/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsackTest.java new file mode 100644 index 000000000000..ef96f16e04f7 --- /dev/null +++ b/src/test/java/com/thealgorithms/dynamicprogramming/BruteForceKnapsackTest.java @@ -0,0 +1,96 @@ +package com.thealgorithms.dynamicprogramming; + +import static org.junit.jupiter.api.Assertions.assertEquals; + +import org.junit.jupiter.api.Test; + +public class BruteForceKnapsackTest { + + @Test + void testKnapSackBasicCase() { + int[] val = {60, 100, 120}; + int[] wt = {10, 20, 30}; + int w = 50; + int n = val.length; + + // The expected result for this case is 220 (items 2 and 3 are included) + assertEquals(220, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackNoItems() { + int[] val = {}; + int[] wt = {}; + int w = 50; + int n = val.length; + + // With no items, the maximum value should be 0 + assertEquals(0, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackZeroCapacity() { + int[] val = {60, 100, 120}; + int[] wt = {10, 20, 30}; + int w = 0; + int n = val.length; + + // With a knapsack of 0 capacity, no items can be included, so the value is 0 + assertEquals(0, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackSingleItemFits() { + int[] val = {100}; + int[] wt = {20}; + int w = 30; + int n = val.length; + + // Only one item, and it fits in the knapsack, so the result is 100 + assertEquals(100, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackSingleItemDoesNotFit() { + int[] val = {100}; + int[] wt = {20}; + int w = 10; + int n = val.length; + + // Single item does not fit in the knapsack, so the result is 0 + assertEquals(0, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackAllItemsFit() { + int[] val = {20, 30, 40}; + int[] wt = {1, 2, 3}; + int w = 6; + int n = val.length; + + // All items fit into the knapsack, so the result is the sum of all values (20 + 30 + 40 = 90) + assertEquals(90, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackNoneFit() { + int[] val = {100, 200, 300}; + int[] wt = {100, 200, 300}; + int w = 50; + int n = val.length; + + // None of the items fit into the knapsack, so the result is 0 + assertEquals(0, BruteForceKnapsack.knapSack(w, wt, val, n)); + } + + @Test + void testKnapSackSomeItemsFit() { + int[] val = {60, 100, 120}; + int[] wt = {10, 20, 30}; + int w = 40; + int n = val.length; + + // Here, only the 2nd and 1st items should be included for a total value of 160 + assertEquals(180, BruteForceKnapsack.knapSack(w, wt, val, n)); + } +}