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WorksheetsDAA quiz2
Total questions: 15
Worksheet time: 44mins
The algorithms like merge sort, quick sort and binary search are based on
Greedy algorithm
Divide and Conquer algorithm
Hash table
Parsing
The step(s) in the Divide and conquer process :
Conquer/Solve
Merge/Combine
Divide/Break
Both B and C
In the Divide and Conquer process, breaking the problem into smaller sub-problems is the responsibility of
Divide/Break
Sorting/Divide
Conquer/Solve
Merge/Combine
(P)->(III),(Q)->(II),(R)->(I)
(P)->(II),(Q)->(I),(R)->(III)
(P)->(I),(Q)->(II),(R)->(III)
(P)->(II),(Q)->(III),(R)->(I)
C11=80, C12=07,C21=15, C22=34
C11=82, C12=26 ,C21=10, C22=34
C11=15, C12=07 ,C21=18, C22=34
C11=26, C12= 10 ,C21=82, C22=34
Selection problem is to:
find the largest number present in the given list
find the smallest number present in the given list
find the kth smallest number present in the given list
none
Which one of the below problem cannot be solved using divide and conquer approach:
mergesort
quicksort
heapsort
binary search
Fractional knapsack problem is solved most efficiently by which of the following algorithm?
Divide and conquer
Dynamic programming
Greedy algorithm
Backtracking
What is the objective of the knapsack problem?
To get maximum profit value in the knapsack
To get minimum profit value in the knapsack
To get maximum weight in the knapsack
To get minimum weight in the knapsack
Given items as {value,weight} pairs {{40,20},{30,10},{20,5}}. The capacity of knapsack=20. Find the maximum value output assuming items to be divisible.
60
80
100
40
1
2
3
all
147
150
135
none
...........................technique is used by solving optimization problems
divide and conquer
greedy method
dynamic programming
both b and c
.................technique doesn't give guarantee that our solution is optimal
greedy method
dynamic programming approach
backtracking
branch and bound
