A Parallelization Based Ant Colony Optimization for Travelling Salesman Problem

Many problems investigated in computer science are also related to problems in daily life. The most famous of these is the Traveling Salesman Problem. This problem is a routing problem and is related to problems such as transportation, networking, vehicle routing. Among the many approaches proposed for TSP so far, the most popular are convolutional algorithms. In this study, a Parallelized Ant Colony Optimization Algorithm is proposed to solve the Traveling Salesman Problem. Thanks to parallelization, the growing time complexity due to the increasing number of cities has been solved. In addition, the effect of the number of colonies on the result was also examined in the study. Experimental results were performed on 5 different problems taken from TSPLIB to validate the developed parallel algorithm. As a result of the study, it has been seen that the increase in the number of colonies increases the time complexity of the algorithm, but thanks to parallelization, it works 50% faster than normal operation.