Ant Colony Optimization Algorithm for Traveling Salesman Problem in Distributing Fertilizer

Fertilization sometimes takes a long time due to the selection of mileage traveled in fertilizer distribution and coupled with the condition of  plantation roads that are partially damaged. The path taken is usually only a path that is memorized and is considered the shortest and optimal. The journey from one location to another by considering the shortest path is included in the problem of graph theory. To determine the shortest path to be traversed, you can use the Ant Colony algorithm, because it is optimal in determining short distances and can measure the minimum accumulated travel time close to optimal. This is a Traveling Salesman Problem (TSP) problem, which is visiting all location points starting from the starting point and ending at the starting point again. This research was conducted on oil palm plantations of PT. Socfindo Bangun Bandar in fertilizer distribution. The sample used is 6 location points which are then solved using the Ant Colony algorithm where this algorithm adopts the workings of ants to get the shortest route. The use of the Ant Colony algorithm in this case is limited to one cycle or one iteration (NC=1) so that the best route is obtained while the first cycle is the fertilizer warehouse (V1) to block 55 (V4) then block 63 (V6) to block 61 (V5) then block 51 (V2) to block 52 (V3) and back again to the fertilizer warehouse (V1), and from this route can be modified again to the opposite route with a distance of 15.71 km. Because the resulting distance is shorter than the usual route, this can speed up the time used by trucks to distribute fertilizer so that trucks can be used by workers to transport harvested palm fruit.