Design and Analysis of the Ant Colony Algorithm to Find the Shortest Route to Sibolga Disaster Locations
Keywords:
Ant Colony Algorithm, Shortest Path, Disaster Location, Route Optimisation, SibolgaAbstract
Determining the shortest route to the disaster location is one of the important aspects in supporting the speed of emergency response. The accuracy in selecting routes can expedite the evacuation process, aid distribution, and the mobilisation of personnel to the disaster site. The city of Sibolga, as an area with a diverse road network, requires a method capable of determining the optimal route effectively and efficiently. This research aims to design and analyse the Ant Colony Optimisation (ACO) algorithm in determining the shortest route to disaster locations in Sibolga. The research methods used include identifying location points and road networks, graph modelling in the form of nodes and weighted edges, designing the Ant Colony algorithm, and testing the route search results based on travel distance. The ACO algorithm works by mimicking the behaviour of ant colonies in finding the best path through pheromone mechanisms and iterative processes. The research results are expected to show that the Ant Colony algorithm is capable of generating the optimal shortest path from the starting point to the disaster location based on the used road network data. Additionally, the analysis of the algorithm's performance provides an overview of the effectiveness of this method in supporting route determination systems in emergency conditions. This research is expected to contribute to the development of decision support systems for disaster management, particularly in accelerating access to disaster locations in the city of Sibolga.
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