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#4367 Enhance Knapsack problem (#4368)

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* Enhance Knapsack problem

* Linter solved

* Linter solved

* Remove DynamicProgrammingKnapsack file, duplicate of Knapsack file

* Add null input testcase

* Linter resolved

* Updated meaningful test names

* Add check for negative weightCapacity

* Linter resolved

* Linter resolved

* Add check for non-positive weight

* Linter resolved

* fix: use proper formatting

* fix: use proper formatting

* fix: use proper formatting (I hope this will work now)

Sorry for the previous mess.

* Code review comments

* Code review comments

* Code review comments

* Code review comments

---------

Co-authored-by: Piotr Idzik <65706193+vil02@users.noreply.github.com>
This commit is contained in:
Manan Solanki 2023-09-20 01:23:53 +05:30 committed by GitHub
parent 26c2465328
commit 12b6c29243
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3 changed files with 123 additions and 61 deletions
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36
src/main/java/com/thealgorithms/dynamicprogramming/DyanamicProgrammingKnapsack.java
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package com.thealgorithms.dynamicprogramming;
// A Dynamic Programming based solution
// for 0-1 Knapsack problem
public class DyanamicProgrammingKnapsack {
// Returns the maximum value that can
// be put in a knapsack of capacity W
static int knapSack(int W, int[] wt, int[] val, int n) {
int i, w;
int[][] K = new int[n + 1][W + 1];
// Build table K[][] in bottom up manner
for (i = 0; i <= n; i++) {
for (w = 0; w <= W; w++) {
if (i == 0 || w == 0) {
K[i][w] = 0;
} else if (wt[i - 1] <= w) {
K[i][w] = Math.max(val[i - 1] + K[i - 1][w - wt[i - 1]], K[i - 1][w]);
} else {
K[i][w] = K[i - 1][w];
}
}
}
return K[n][W];
}
// 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));
}
}

67
src/main/java/com/thealgorithms/dynamicprogramming/Knapsack.java
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package com.thealgorithms.dynamicprogramming;
import java.util.Arrays;
/**
* A DynamicProgramming based solution for 0-1 Knapsack problem
* A Dynamic Programming based solution for the 0-1 Knapsack problem.
* This class provides a method, `knapSack`, that calculates the maximum value that can be
* obtained from a given set of items with weights and values, while not exceeding a
* given weight capacity.
*
* @see <a href="https://en.wikipedia.org/?title=0-1_Knapsack_problem">0-1 Knapsack Problem </a>
*/
public class Knapsack {
public final class Knapsack {
private static int knapSack(int W, int[] wt, int[] val, int n) throws IllegalArgumentException {
if (wt == null || val == null) {
throw new IllegalArgumentException();
private Knapsack() {
}
private static void throwIfInvalidInput(final int weightCapacity, final int[] weights, final int[] values) {
if (weightCapacity < 0) {
throw new IllegalArgumentException("Weight capacity should not be negative.");
}
int i, w;
int[][] rv = new int[n + 1][W + 1]; // rv means return value
if (weights == null || values == null || weights.length != values.length) {
throw new IllegalArgumentException("Input arrays must not be null and must have the same length.");
}
if (Arrays.stream(weights).anyMatch(w -> w <= 0)) {
throw new IllegalArgumentException("Input array should not contain non-positive weight(s).");
}
}
// Build table rv[][] in bottom up manner
for (i = 0; i <= n; i++) {
for (w = 0; w <= W; w++) {
if (i == 0 || w == 0) {
rv[i][w] = 0;
} else if (wt[i - 1] <= w) {
rv[i][w] = Math.max(val[i - 1] + rv[i - 1][w - wt[i - 1]], rv[i - 1][w]);
} else {
rv[i][w] = rv[i - 1][w];
/**
* Solves the 0-1 Knapsack problem using Dynamic Programming.
*
* @param weightCapacity The maximum weight capacity of the knapsack.
* @param weights An array of item weights.
* @param values An array of item values.
* @return The maximum value that can be obtained without exceeding the weight capacity.
* @throws IllegalArgumentException If the input arrays are null or have different lengths.
*/
public static int knapSack(final int weightCapacity, final int[] weights, final int[] values) throws IllegalArgumentException {
throwIfInvalidInput(weightCapacity, weights, values);
// DP table to store the state of the maximum possible return for a given weight capacity.
int[] dp = new int[weightCapacity + 1];
for (int i = 0; i < values.length; i++) {
for (int w = weightCapacity; w > 0; w--) {
if (weights[i] <= w) {
dp[w] = Math.max(dp[w], dp[w - weights[i]] + values[i]);
}
}
}
return rv[n][W];
}
// Driver program to test above function
public static void main(String[] args) {
int[] val = new int[] {50, 100, 130};
int[] wt = new int[] {10, 20, 40};
int W = 50;
System.out.println(knapSack(W, wt, val, val.length));
return dp[weightCapacity];
}
}

81
src/test/java/com/thealgorithms/dynamicprogramming/KnapsackTest.java Normal file
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package com.thealgorithms.dynamicprogramming;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertThrows;
import org.junit.jupiter.api.Test;
public class KnapsackTest {
@Test
public void testKnapSackBasic() {
int[] weights = {2, 3, 4, 5};
int[] values = {3, 4, 5, 6};
int weightCapacity = 5;
int expected = 7; // Maximum value should be 7 (items 1 and 4).
int result = Knapsack.knapSack(weightCapacity, weights, values);
assertEquals(expected, result);
}
@Test
public void testKnapSackEmpty() {
int[] weights = {};
int[] values = {};
int weightCapacity = 10;
int expected = 0; // With no items, the result should be 0.
int result = Knapsack.knapSack(weightCapacity, weights, values);
assertEquals(expected, result);
}
@Test
public void testKnapSackNoCapacity() {
int[] weights = {2, 3, 4};
int[] values = {3, 4, 5};
int weightCapacity = 0;
int expected = 0; // With no capacity, the result should be 0.
int result = Knapsack.knapSack(weightCapacity, weights, values);
assertEquals(expected, result);
}
@Test
public void testKnapSackMaxCapacity() {
int[] weights = {2, 3, 4, 5};
int[] values = {3, 4, 5, 6};
int weightCapacity = 10;
int expected = 13; // Maximum value should be 13 (items 1, 3, and 4).
int result = Knapsack.knapSack(weightCapacity, weights, values);
assertEquals(expected, result);
}
@Test
public void testKnapSackThrowsForInputsOfDifferentLength() {
int[] weights = {2, 3, 4};
int[] values = {3, 4, 5, 6}; // Different length values array.
int weightCapacity = 5;
assertThrows(IllegalArgumentException.class, () -> { Knapsack.knapSack(weightCapacity, weights, values); });
}
@Test
public void testKnapSackThrowsForNullInputs() {
int[] weights = {2, 3, 4};
int[] values = {3, 4, 6};
int weightCapacity = 5;
assertThrows(IllegalArgumentException.class, () -> { Knapsack.knapSack(weightCapacity, null, values); });
assertThrows(IllegalArgumentException.class, () -> { Knapsack.knapSack(weightCapacity, weights, null); });
}
@Test
public void testKnapSackThrowsForNegativeCapacity() {
int[] weights = {2, 3, 4, 5};
int[] values = {3, 4, 5, 6};
int weightCapacity = -5;
assertThrows(IllegalArgumentException.class, () -> { Knapsack.knapSack(weightCapacity, weights, values); });
}
@Test
public void testKnapSackThrowsForNegativeWeight() {
int[] weights = {2, 0, 4};
int[] values = {3, 4, 6};
int weightCapacity = 5;
assertThrows(IllegalArgumentException.class, () -> { Knapsack.knapSack(weightCapacity, weights, values); });
}
}