Answer: True
Explanation:
Subset sum problem and Knapsack problem can be solved using dynamic programming.
In case of Knapsack problem there is a set of weights associative with objects and a set of profits associated with each object and a total capacity of knapsack let say C. With the help of dynamic programming we try to include object's weight such that total profit is maximized without fragmenting any weight of objects and without exceeding the capacity of knapsack, it is also called as 0/1 knapsack problem.
Similar to knapsack problem, in subset sum problem there is set of items and a set of weights associated with the items and a capacity let say C, task is to choose the subset of items such that total sum of weights associated with items of subset is maximized without exceeding the total capacity.
On the basis of above statements we can say that subset sum problem is generalization of knapsack problem.
Yum sounds like a good idea
Answer:
All except It makes a company look modern.
Explanation:
Motorcycles have two or three wheels, a seat for the rider and at lease a 70 horse-powered engine.
Answer:
Explanation:
The code that would best accomplish this task using a while loop would be the following:
list1 = [8, 3, 4, 5, 6, 7, 9]
accum = 0
n = 0
while n < 7:
accum += list1[n]
n += 1
This code will continue throughout the list1 array and add every value to the accum variable.
