Undergrad Polynomial vs. Exponential time

  • Thread starter Thread starter senmeis
  • Start date Start date
  • Tags Tags
    Complexity
Click For Summary
Polynomial time algorithms offer manageable performance increases with input size, while exponential time algorithms experience drastic growth, making them impractical for large datasets. The discussion highlights Strassen's matrix multiplication as an example of a polynomial improvement that significantly reduces computational complexity. In contrast, NP-complete problems, such as the traveling salesman problem, illustrate the stark difference in feasibility between polynomial and exponential solutions in real-world applications. Even a modest input size can lead to exponential algorithms becoming unmanageable, emphasizing the importance of choosing efficient algorithms. Understanding these differences is crucial for optimizing performance in various fields, including logistics and software development.
senmeis
Messages
75
Reaction score
2
Hi,

How much time difference can be expected between polynomial and exponential time?
 
Mathematics news on Phys.org
Guessing OP is referring to solving times, like sorting algorithms.

Algorithms with polynomial run times proceed at a manageable rate, whereas algorithms with exponential run times often double their run times with each additional element, rapidly becoming unmanageable.
 
Last edited:
  • Agree
Likes FactChecker
senmeis said:
Hi,

How much time difference can be expected between polynomial and exponential time?
This is only relevant for large input lengths. An example. Strassen's matrix multiplication has brought the number of multiplications, which were time-consuming in relation to additions, from ##n^3## to ##n^{2.8}##. I've heard rumors that this was enough to implement the algorithm in airplane software. And this was only a polynomial improvement.

If you look at NP complete problems like the travelling salesman problem, which has many real-world applications like staffing in industries such as airlines, hospitals, or logistics, where a large number of persons and regulations have to be juggled, you get a tremendous benefit between polynomial and exponential.

##100^5=10^{10}## but ##e^{100}\sim 10^{43}=1000\cdot 10^{10}\cdot 10^{10}\cdot 10^{10}\cdot 10^{10}.## So even ##n=100## can vary between doable and hopeless.
 
Last edited:
  • Like
Likes FactChecker
Here is a little puzzle from the book 100 Geometric Games by Pierre Berloquin. The side of a small square is one meter long and the side of a larger square one and a half meters long. One vertex of the large square is at the center of the small square. The side of the large square cuts two sides of the small square into one- third parts and two-thirds parts. What is the area where the squares overlap?

Similar threads

  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 10 ·
Replies
10
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 1 ·
Replies
1
Views
4K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
  • · Replies 19 ·
Replies
19
Views
4K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 0 ·
Replies
0
Views
2K