#include<stdio.h>
#include<conio.h>
int w[10],p[10],v[10][10],n,i,j,cap,x[10]={0};
int max(int i,int j)
{
return ((i>j)?i:j);
}
int knap(int i,int j)
{
int value;
if(v[i][j]<0)
{
if(j<w[i])
value=knap(i-1,j);
else
value=max(knap(i-1,j),p[i]+knap(i-1,j-w[i]));
v[i][j]=value;
}
return(v[i][j]);
}
void main()
{
int profit,count=0;
clrscr();
printf("\nEnter the number of elements\n");
scanf("%d",&n);
printf("Enter the profit and weights of the elements\n");
for(i=1;i<=n;i++)
{
printf("For item no %d\n",i);
scanf("%d%d",&p[i],&w[i]);
}
printf("\nEnter the capacity \n");
scanf("%d",&cap);
for(i=0;i<=n;i++)
for(j=0;j<=cap;j++)
if((i==0)(j==0))
v[i][j]=0;
else
v[i][j]=-1;
profit=knap(n,cap);
i=n;
j=cap;
while(j!=0&&i!=0)
{
if(v[i][j]!=v[i-1][j])
{
x[i]=1;
j=j-w[i];
i--;
}
else
i--;
}
printf("Items included are\n");
printf("Sl.no\tweight\tprofit\n");
for(i=1;i<=n;i++)
if(x[i])
printf("%d\t%d\t%d\n",++count,w[i],p[i]);
printf("Total profit = %d\n",profit);
getch();
}
yes
no.
Perform encryption on the following PT using RSA and find the CT p = 3; q = 11; M = 5
Please visit http://talentsealed.blogspot.com/2009/10/to-find-smallest-among-three-using.htmlfor answer.
Yes. More generally, every algorithm (defined as a sequence of finite steps to solve a problem that can be easily understood by a human) can be converted into machine code such that the algorithm can be understood by a machine. The C programming language is just one such method of converting algorithms into working machine code.
yes
You don't write an algorithm for a C++ program, unless you are documenting the C++ program after-the-fact. The normal procedure is to write the algorithm first, in a language independent fashion, and then translate that stated algorithm into C++ code, or into whatever language you wish.
no.
The greedy algorithm for the knapsack problem involves selecting items based on their value-to-weight ratio, prioritizing items with the highest ratio first. This approach aims to maximize the value of items placed in the knapsack while staying within its weight capacity. By iteratively selecting the most valuable item that fits, the greedy algorithm can provide a near-optimal solution for the knapsack problem.
reymond rillera reymond rillera
The greedy algorithm is used in solving the knapsack problem efficiently by selecting items based on their value-to-weight ratio, prioritizing those with the highest ratio first. This helps maximize the value of items that can fit into the knapsack without exceeding its weight capacity.
The time complexity of the knapsack greedy algorithm for solving a problem with a large number of items is O(n log n), where n is the number of items.
They are bosom-friends.
Not used
The C code for Prim's algorithm can be found in the following link. https://sites.google.com/site/itstudentjunction/lab-programming-solutions/data-structures-programs/program-to-find-minimal-spanning-tree-using--prims-algorithm
The knapsack greedy algorithm is used to solve optimization problems where resources need to be allocated efficiently. It works by selecting items based on their value-to-weight ratio, prioritizing those that offer the most value while staying within the weight limit of the knapsack. This algorithm helps find the best combination of items to maximize the overall value while respecting the constraints of the problem.
The program itself is the solution. All programs are a solution to a given problem; that's the entire point of writing a program, to solve a problem. The program's algorithm specifies how the problem is solved and it's the programmer's job to convert that algorithm into working code.