Open AccessDetermination of the tourist route in Malang Raya by using ant colony optimization
Author(s) -
Ahmad Rozidi,
Salwa Anam,
U Habibah
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1872/1/012003
Subject(s) - ant colony optimization algorithms , computer science , mathematical optimization , vehicle routing problem , tourism , heuristics , operations research , particle swarm optimization , dual (grammatical number) , heuristic , routing (electronic design automation) , mathematics , geography , art , computer network , literature , archaeology
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.