Abstract
This study aims to build a shortest path simulation program on the complete graph K_20. The data of distance in this simulation was determined randomly with the provision of a value of 0-100. The simulation conducted was an algorithm calculation used parameter values with different initial pheromone conditions. The parameters in the Ant Colony Optimization Algorithm are set with alpha = 1, beta = 2, the initial pheromone condition = 0,0001 for the first simulation; alpha = 1, beta = 2, initial pheromone = 1 for the second simulation; and alpha value = 1, beta = 5, initial pheromone condition = 0,00000001 for the third simulation. The simulation results showed that if the value of the initial pheromone condition used gets greater, the value of the temporary output gets greater. Even though the initial pheromone condition was different, the shortest path obtained with distance data used in this study is the same, namely 15-14-1-3-20-12-16-6-18-10-9-13-11-7-8-4-2-17-5-19 with length 613 (in kilometers). [THE SHORTEST PATH SIMULATION IN COMPLETE GRAPHS USING THE ANT COLONY OPTIMIZATION ALGORITHM](J. Sains Indon., 42(2): 44-51, 2018) Keywords: Ant Colony Optimization Algorithm, Complete Graph, Shortest Path
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
