IMPROVING VIRUS COLONY SEARCH PERFORMANCE ON TRAVELLING SALESMAN PROBLEM CASE

• Main Author: Yulfiandi Rachmat, Zilfikri
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/54334
• Institution: Institut Teknologi Bandung

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.