Search Application of Alternative Road for Tourism Location in Jember Regency – East Java by Using Ant Colony System (ACS)
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 9
Abstract
Everyone needs a tourist attraction to add knowledge and experience. Jember city is one of the city that has many tourist attractions. The tourists who are going to the attractions need a lot of paths to take, so it takes a method to choose the shortest path. There are some solutions to solve the shortest path search which has been done a lot. However, the solution has not provided satisfactory success, so various improvement efforts need to be done. In this research, the shortest path search is using Ant Colony System (ACS) method. The ACS method is one of the heuristic methods that can provide the optimal solution to find the shortest path on the way from the nest to the food source or destination. The performance process of the ACS is to move from one node to the next with high pheromone evaporation to choose the best and optimal solution based on the compilation of the visit path from each ant to each city. Ant colony travels continuously until all the cities one by one which is visited or have occupied the tabu list. This method uses tabu list to store a set of recently evaluated solutions, and the results will be adjusted first with the contents of the taboo list to see if the solution has been achieved or not. When the solution is reached then the solution will not be evaluated again in the next iteration. Various trials are underway to prevent the retrieval process in the available traced solution space. The results show that ACS method developed in this research is able to find the determination in determining the journey with the shortest path from and to the tourist object in Jember so that it can be considered in decision making to show the path that will be passed and the efficiency of time, cost and energy. The quality of success is obtained using parameters q0 = 0.1, α = 0.2, β = 2, ρ = 0.2 with the number of ants and many cycles.
Authors and Affiliations
Devie Rosa Anamisa, M. Ali Syakur, Aeri Rachmad
Keywords
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