Determination of the tourist route in Malang Raya by using ant colony optimization

Abstract

Malang Raya is one of the most popular tourist destinations in Indonesia and has many interesting tourist attractions. Tourists need much time to visit all the tourist attractions. It is not possible to visit all the tourist attractions since vacation time is limited. Therefore, the method for determining the tourist route with the minimum time and satisfy the constraint is needed. The problem is Vehicle Routing Problem (VRP) and can be solved by meta-heuristic. There are several meta-heuristics that can be used to solve VRP, for example Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Ant Colony Optimization (ACO). ACO has the advantage of a good positive feedback mechanism when compared to GA and PSO. For this reasons, this paper presents the determination of tourist route in Malang Raya by using ACO. However, ACO tends to solution stagnation. In this paper, the solution stagnation of ACO will be solved by applying the dual pheromone tables. The results show that ACO with dual pheromone tables can solve the problem of determining tourist routes in Malang Raya well in terms of quality of solution because ACO with dual pheromone tables can obtain better results in the time cost of the route than standard ACO.