HEURISTIC ALGORITHM FOR RING TOPOLOGY NETWORK OPTIMIZATION
The Travelling Salesman Problem (TSP) is to find a routing of a salesman who starts from a home location, visits a prescribed set of cities and returns to the original location such in such a way that the total distance travelled is minimum and each city visited exactly once. TSP has a widespread...
Saved in:
Main Author: | |
---|---|
Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/50576 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | The Travelling Salesman Problem (TSP) is to find a routing of a salesman who
starts from a home location, visits a prescribed set of cities and returns to the
original location such in such a way that the total distance travelled is minimum
and each city visited exactly once. TSP has a widespread application value in real
life. In telecommunication networks it is important to determine the shortest route
(cost) in designing the ring topology. So an efficient solution to this problem can
reduces deployment costs. TSP is a classic problem that is simple but difficult to
solve conventionally. That have intrigued researchers to explore and develop
algorithms for solving TSP problems. Some algorithms that have been found
include brute force algorithm, ant colony optimization algorithm (ACO), greedy
algorithm, Greedy Randomized Adaptive Search Procedure (GRASP). Brute force
Algorithm is the easiest and most expensive solution for TSP. This algorithm try all
possibilities, so it generates an absolute minimum value but takes a very long
execution time for a big number of nodes. Other algorithms use the heuristic
method, so it does not always provide an optimal solution although it can save
execution time compared to the brute force algorithm. Research for the
development of heuristic algorithms is still very open. This study focuses on getting
the solution to the Traveling Salesman Problem with the heuristic method so it can
produce algorithms with fast execution times and accurate results close to the
absolute minimum value, so it can be implemented in network planning. This
algorithm is a development of an existing algorithm. This algorithm successfully
corrects the shortcomings of the previous algorithm, which is a long computational
time. In this study python programming languages are used, Net2Plan network
simulator is used for simulations. The results showed that this algorithm in some
data could outperform some other algorithms both in terms of execution time and
the resulting minimum value solution.
|
---|