Analisis Perbandingan Algoritma ACO-TS dan ACO-SMARTER Dalam Menyelesaikan Traveling Salesman Problem

Abstract

The research conducted is the Comparative Analysis of the ACO-TS and ACO-SMARTER Algorithms in Solving the Traveling Salesman Problem where the problem to be solved is the traveling salesman problem (TSP). The purpose of this study is to hopefully be able to provide a comparison result of running time and the shortest distance between the ACO-TS algorithm and the ACO-SMARTER algorithm in solving the TSP. The test results show that the combination of the Ant Colony Optimization (ACO) algorithm and the Tabu Search (TS) algorithm is better in terms of achieving the optimum path and running time than the ACO and ACO-SMARTER algorithms in solving the Traveling Salesman Problem. The Tabu Search algorithm in the ACO algorithm acts as a controller for the routes that have been selected so that they are not processed again by the same ant. This will certainly make the ACO-TS algorithm faster in processing data because there is no data on the same route in the next round, where from 200 datasets the running time is obtained at ACO 11.5 seconds and the optimum distance is 76687, ACO SMARTER 8.5 seconds and the optimum distance is 74496 while the ACO-TS only takes 2.9 seconds and the optimum distance is 70558