IMPROVING VIRUS COLONY SEARCH PERFORMANCE ON TRAVELLING SALESMAN PROBLEM CASE
The Virus Colony Search algorithm is a nature-inspired algorithm, simple yet effective enough to solve optimization problems. The algorithm has 3 main parts, Viruses Diffusion, Host Infection, and Immune Response. The Viruses Diffusion‘s part uses the Gaussian Random Walk as the main component to...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/54334 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | The Virus Colony Search algorithm is a nature-inspired algorithm, simple yet
effective enough to solve optimization problems. The algorithm has 3 main parts,
Viruses Diffusion, Host Infection, and Immune Response. The Viruses Diffusion‘s
part uses the Gaussian Random Walk as the main component to calculate. In this
paper, using the implementation of the Global Random Walk in the Viruses
Diffusion’s part and also to prove that The Virus Colony Search Algorithm able to
solve the Traveling Salesman Problem, in this case by using the Symmetric-TSP.
The conducted experiments divided into four parts, experiments by the number of
virus populations, experiments by the size of the problem dimensions or the number
of nodes, experiments of algorithm’s execution time, and experiments of
comparison of routes. The result of this research, it is proven that The Virus Colony
Search algorithm was able to solve the Travelling Salesman Problem and also by
using the Global Random Walk on the Search Colony Virus Algorithm it is able to
improve performance, especially on the aspect of the required iterations.
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