Ant Colony Optimization for Traveling Tourism Problem on Timor Island East Nusa Tenggara

Abstract

Timor island consists of five districts and one city, namely Kupang District, South Central Timor District, North Central Timor, Belu District, Malaka District, and Kupang City. On the Timor island, it has natural tourist destinations, culinary tours, cultural and historical attractions most on the island of Timor. The Ant Colony Optimization (ACO) Algorithm is very unique compared to the other nearby search algorithm, this algorithm adopted because of Ant Colony who were looking for food from the nest to food sources by leaving a footprint called Pheromone. Mapping system algorithm using ant, tourist sites can show the shortest route between two points is desired. Ants algorithm proved to be applied in determining the optimum route, but still has the disadvantage of dependence on the parameter value is not maximized. From the test results based on parameters of the cycle and the number of ants affects the simulation time, for ant algorithm parameters. From the test results based on the parameters, α and β affects, number of node, the simulation time and the shortest distance varying toward the destination even if the starting location and ending on the same location.