Fractional Knapsack Problem in DSA C++ - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is the main goal of the Fractional Knapsack Problem?

To maximize the total value of items placed in a knapsack with a fixed weight capacity, allowing fractions of items to be taken.

beginner

Why can we take fractions of items in the Fractional Knapsack Problem but not in the 0/1 Knapsack Problem?

Because the problem allows dividing items into smaller parts, so you can take any fraction of an item, unlike 0/1 Knapsack where items are indivisible.

intermediate

What greedy strategy is used to solve the Fractional Knapsack Problem?

Sort items by their value-to-weight ratio in descending order and pick items starting from the highest ratio until the knapsack is full.

intermediate

In the Fractional Knapsack Problem, what happens when the next item's weight exceeds the remaining capacity?

We take only the fraction of the item that fits into the remaining capacity to maximize value.

intermediate

What is the time complexity of the Fractional Knapsack Problem solution using sorting?

O(n log n) due to sorting the items by their value-to-weight ratio, where n is the number of items.

What is the key difference between the Fractional Knapsack and 0/1 Knapsack problems?

A 0/1 Knapsack allows fractions, Fractional Knapsack does not.

B Fractional Knapsack allows taking parts of items, 0/1 Knapsack does not.

C Both allow fractions of items.

D Neither allows fractions of items.

Fractional Knapsack allows dividing items and taking fractions, while 0/1 Knapsack requires taking whole items only.

Which greedy criterion is used to select items in the Fractional Knapsack Problem?

A Lowest weight first

B Highest value first

C Highest value-to-weight ratio first

D Random selection

Items are chosen based on the highest value-to-weight ratio to maximize value per unit weight.

If the knapsack capacity is 50 and the next item weighs 30 but only 20 capacity remains, what do we do?

A Take a fraction of the item that fits (20 units)

B Take the whole item anyway

C Remove some items already taken

D Skip the item

We take only the fraction of the item that fits into the remaining capacity to maximize total value.

What is the first step in solving the Fractional Knapsack Problem?

A Sort items by value-to-weight ratio descending

B Sort items by value descending

C Sort items by weight ascending

D Pick items randomly

Sorting by value-to-weight ratio descending ensures we pick the most valuable items per unit weight first.

What is the overall time complexity of the Fractional Knapsack solution?

A O(log n)

B O(n)

C O(n^2)

D O(n log n)

Sorting the items by value-to-weight ratio takes O(n log n), which dominates the solution's time complexity.

Explain the greedy approach to solve the Fractional Knapsack Problem step-by-step.

Think about how to get the most value per weight unit first.

Describe the difference between Fractional Knapsack and 0/1 Knapsack problems and why the greedy method works for one but not the other.

Consider divisibility of items and how it affects solution strategies.

Practice

1. What is the main goal of the Fractional Knapsack Problem?

easy

A. Maximize total value by taking fractions of items within weight limit

B. Maximize total value by taking whole items only

C. Minimize total weight of items selected

D. Find the minimum number of items to fill the knapsack

Solution

1. Step 1: Understand problem goal

   The fractional knapsack problem allows taking parts of items to maximize value within a weight limit.

2. Step 2: Compare options

   Maximize total value by taking fractions of items within weight limit correctly states maximizing value by fractions; others are about whole items or minimizing weight, which are incorrect.

3. Final Answer:

   Maximize total value by taking fractions of items within weight limit -> Option A

4. Quick Check:

   Fractional knapsack = maximize value with fractions [OK]

Hint: Fractional knapsack allows partial items for max value [OK]

Common Mistakes:

• Confusing fractional knapsack with 0/1 knapsack
• Thinking only whole items can be taken
• Assuming problem minimizes weight

2. Which of the following C++ code snippets correctly sorts items by value-to-weight ratio in descending order for fractional knapsack?

easy

A. std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return a.weight > b.weight; });

B. std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return (a.value / a.weight) > (b.value / b.weight); });

C. std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return a.value < b.value; });

D. std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return (a.weight / a.value) > (b.weight / b.value); });

Solution

1. Step 1: Identify correct sorting criteria

   We must sort by value-to-weight ratio descending: (value/weight) high to low.

2. Step 2: Check each option

   std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return (a.value / a.weight) > (b.value / b.weight); }); sorts by (value/weight) descending correctly. Others sort by wrong ratio or by value or weight alone.

3. Final Answer:

   std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return (a.value / a.weight) > (b.value / b.weight); }); -> Option B

4. Quick Check:

   Sort by value/weight descending = std::sort(items.begin(), items.end(), [](auto &a, auto &b) { return (a.value / a.weight) > (b.value / b.weight); }); [OK]

Hint: Sort by value/weight ratio descending for greedy pick [OK]

Common Mistakes:

• Sorting by weight/value instead of value/weight
• Sorting ascending instead of descending
• Sorting by value or weight alone

3. What is the output of the following C++ code snippet for fractional knapsack?

struct Item { int value; int weight; };
std::vector<Item> items = {{60, 10}, {100, 20}, {120, 30}};
int W = 50;
// Assume items sorted by value/weight descending
float totalValue = 0;
int capacity = W;
for (auto &item : items) {
  if (item.weight <= capacity) {
    capacity -= item.weight;
    totalValue += item.value;
  } else {
    totalValue += item.value * ((float)capacity / item.weight);
    break;
  }
}
std::cout << totalValue << std::endl;

medium

A. 180

B. 220

C. 200

D. 240

Solution

1. Step 1: Calculate value/weight ratios and sort

   Ratios: 60/10=6, 100/20=5, 120/30=4. Sorted order: {60,10}, {100,20}, {120,30}.

2. Step 2: Pick items greedily until capacity 50

   Take first item fully: capacity=50-10=40, totalValue=60. Take second item fully: capacity=40-20=20, totalValue=60+100=160. Take third item fraction: fraction=20/30=2/3, value=120*(2/3)=80. Total value=160+80=240.

3. Final Answer:

   240 -> Option D

4. Quick Check:

   Sum values with fractions = 240 [OK]

Hint: Pick full items then fraction of next to fill capacity [OK]

Common Mistakes:

• Not sorting items by value/weight ratio
• Taking items in wrong order
• Incorrect fraction calculation

4. Identify the bug in this fractional knapsack code snippet:

float fractionalKnapsack(int W, std::vector<Item> &items) {
  std::sort(items.begin(), items.end(), [](auto &a, auto &b) {
    return (a.value / a.weight) > (b.value / b.weight);
  });
  float totalValue = 0;
  int capacity = W;
  for (auto &item : items) {
    if (item.weight < capacity) {
      capacity -= item.weight;
      totalValue += item.value;
    } else {
      totalValue += item.value * ((float)capacity / item.weight);
      break;
    }
  }
  return totalValue;
}

medium

A. Should use <= instead of < in if condition to include full item when equal

B. Sorting comparator divides integers causing integer division error

C. Capacity variable should be float, not int

D. Missing return statement at end of function

Solution

1. Step 1: Analyze if condition for full item inclusion

   The condition uses 'item.weight < capacity', so if weight equals capacity, it skips full inclusion and takes fraction.

2. Step 2: Correct condition to include full item when weight equals capacity

   Changing to 'item.weight <= capacity' allows taking full item if it fits exactly, which is correct behavior.

3. Final Answer:

   Should use <= instead of < in if condition to include full item when equal -> Option A

4. Quick Check:

   Use <= to include full item when weight equals capacity [OK]

Hint: Use <= to include full item when weight equals capacity [OK]

Common Mistakes:

• Using < instead of <= causing partial fraction unnecessarily
• Ignoring integer division in comparator (not an issue here)
• Wrong variable types for capacity

5. Given items with values and weights: {value: 40, weight: 2}, {value: 100, weight: 20}, {value: 50, weight: 10}, and knapsack capacity 25, what is the maximum value achievable using fractional knapsack?

hard

A. 160

B. 150

C. 155

D. 140

Solution

1. Step 1: Calculate value/weight ratios and sort items

   Ratios: - 40/2 = 20 - 100/20 = 5 - 50/10 = 5 Sorted order: {40,2}, {100,20}, {50,10} (40,2 first due to highest ratio)

2. Step 2: Pick items greedily until capacity 25

   Take first item fully: capacity=25-2=23, totalValue=40. Take second item fully: capacity=23-20=3, totalValue=40+100=140. Take third item fraction: fraction=3/10=0.3, value=50*0.3=15. Total value=140+15=155.

3. Step 3: Re-check sorting for tie in ratio

   Since second and third items have same ratio, order can be swapped. Try picking {40,2}, {50,10}, {100,20}: Take {40,2}: capacity=23, value=40 Take {50,10}: capacity=13, value=90 Take fraction of {100,20}: fraction=13/20=0.65, value=100*0.65=65 Total=40+50+65=155 (same)

4. Final Answer:

   155 -> Option C

5. Quick Check:

   Pick highest ratio items fully, fraction last = 155 [OK]

Hint: Sort by ratio, pick full items, fraction last to fill capacity [OK]

Common Mistakes:

• Not sorting by value/weight ratio correctly
• Picking items in wrong order
• Ignoring fractional part calculation