ANALYSIS AND COMMUNITY DETECTION OF FLIGHT ROUTES NETWORK OF SEVERAL AIRLINES IN INDONESIA USING A COMBINATION OF GENETIC ALGORTHM AND SIMULATED ANNEALING

• Main Author: Pramayoga, Adhiyatma
• Format: Final Project
• Language: Indonesia
• Subjects: Fisika
• Online Access: https://digilib.itb.ac.id/gdl/view/41878
• Institution: Institut Teknologi Bandung

Complex network or often also referred to as graph in one of the models of complex system. Generally, complex network is formed from two main forming systems. The two main forming systems are node and edge. One of the research of complex network that quite developed is community detection. Community detection is used to understand many networks in real life. One of the most widely developed methods to detect community is Genetic Algorithm. Genetic Algorithm is search algorithm which is based on the principle of natural selection in genetic science to develop solutions to solve problems. However, Genetic Algorithm has some weaknesses that can be handled by using the global optimum searching methods, one of them is Simulated Annealing. Simulated Annealing was inspired by the principle of thermodynamics in the annealing process found in metallurgy. This Final Project uses a method of combining Genetic Algorithm and Simulated Annealing to find the global optimum value. The real network used for community detection in this Final Project is a network of flight routes for several airlines in Indonesia. The purpose of community detection of network flight routes is to find airports or cities as hub nodes of an airline. Hub node is a city or an airport that connecting a city to another city or an airport to another airport.