Virtual Labs

Greedy Algorithms 2: Fractional Knapsack Problem

After starting the simulation, why are items processed in descending order of value-to-weight ratio?

a: To minimize the number of items selected Explanation

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b: To ensure maximum value is obtained per unit weight Explanation

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c: To reduce execution time only Explanation

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d: To match the input order Explanation

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What does the knapsack fill indicator represent during the simulation?

a: Total value accumulated so far Explanation

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b: Number of items selected Explanation

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c: Current weight filled relative to maximum capacity Explanation

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d: Execution time of the algorithm Explanation

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In Manual Mode, what happens when the selected item cannot fully fit into the remaining knapsack capacity?

a: The item is skipped Explanation

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b: The simulation terminates immediately Explanation

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c: A fraction of the item is added to fill the remaining capacity Explanation

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d: The item is added fully, exceeding capacity Explanation

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Why does the simulation stop automatically once the knapsack reaches full capacity?

a: No more items are left Explanation

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b: Further addition would violate the capacity constraint Explanation

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c: The maximum value has already been displayed Explanation

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d: The animation speed reaches zero Explanation

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In the Results table, what does a value like "66.7%" taken for an item indicate?

a: The item was skipped Explanation

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b: The item was fully selected Explanation

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c: Only a fraction of the item was added to the knapsack Explanation

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d: The item had the highest ratio Explanation

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During Auto Play mode, which component explains the decision taken at each step of the algorithm?

a: Items Panel Explanation

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b: Knapsack Panel Explanation

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c: Execution Log Explanation

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d: Input Parameters panel Explanation

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If two items have the same value-to-weight ratio, how does the simulation handle their selection?

a: Both are ignored Explanation

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b: They are selected randomly Explanation

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c: Any order can be chosen without affecting optimality Explanation

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d: The heavier item is always selected first Explanation

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Why does the Fractional Knapsack simulation always produce an optimal solution using a greedy approach?

a: Because all combinations are tested Explanation

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b: Because the problem satisfies the greedy choice property Explanation

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c: Because the knapsack size is fixed Explanation

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d: Because recursion is used internally Explanation

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Which observation from the simulation distinguishes Fractional Knapsack from 0/1 Knapsack?

a: Items are sorted before selection Explanation

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b: Dynamic programming is used Explanation

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c: Items can be partially selected Explanation

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d: Execution time is lower Explanation

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In the simulation, what happens when the knapsack capacity is greater than the sum of all item weights?

a: Items are repeatedly selected until the knapsack is full Explanation

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b: The simulation selects all items once and stops with unused capacity Explanation

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c: The item with the highest value-to-weight ratio is duplicated Explanation

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d: Fractional selection is forced to fill the remaining capacity Explanation

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