LKS - Large Knapsack
The knapsack problem or rucksack problem is a problem in combinatorial optimization: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as large as possible. It derives its name from the problem faced by someone who is constrained by a fixed-size knapsack and must fill it with the most valuable items.
Just implement 0/1 Knapsack.
First line contains two integers K and N, where K in the maximum knapsack size and N is the number of items. N lines follow where ith line describes ith item in the form vi and wi where vi is the value and wi is the weight of ith item.
Output a single number - maximum value of knapsack. (All operations and the answer are guaranteed to fit in signed 32-bit integer.)
Time limit changed to 2s on 02.07.11.
Input: 10 3 7 3 8 8 4 6 Output: 11
K <= 2000000
N <= 500
Vi <= 10^7
Wi <= 10^7
For all of you wondering how to get 0.0s learn branch and bound algorithm very useful and fun
*Edit: nevermind, i used a different compiler and it was fine.
This should help if you stuck for a long time. See the second program in this link : https://www.geeksforgeeks.org/space-optimized-dp-solution-0-1-knapsack-problem/
use the optimized knapsack
How are people getting 0.00 seconds on this one . My space optimised 0-1 knapsack dp of order O(nW) took 1 second even in C.
unbelievable turned long long to int got ac??
normal knapsack...N*K time complexity...i think input file doesn't contain k = 2000000 and n=500....cz if so then n*k = 1e9...-> tle
LONG LONG INT GAVE TLE INT 1.54 Sec
Space optimized java solution gives tle. Same code accepted in cpp.
I thought it need some complicated optimization, but it turns out not.