Ant Colony Optimization (ACO) Algorithm for Determining The Nearest Route Search in Distribution of Light Food Production

• Published in: Journal of physics. Conference series Vol. 1566; no. 1; pp. 12045 - 12051
• Main Authors: Fahmi, H, Zarlis, M, Nababan, E B, Sihombing, P
• Format: Journal Article
• Language: English
• Published: IOP Publishing 01.06.2020
• ISSN: 1742-6588; 1742-6596; 1742-6596
• DOI: 10.1088/1742-6596/1566/1/012045

At this time the development of technology that forces everything must move fast, the efficiency of time becomes a measure of the success of a distribution or production. the continuity of production and the success of production itself is related to distribution. When the distribution fails, production will fail. Indonesian people especially in North Sumatra often consume snacks when free time and snacks are the most consumed food by the Indonesian population until now the production of snacks in Indonesia rose to 50% in 2019, causing the food production to have a concept in timely distribution without experiencing delays in distributing goods that have been produced. One of the expeditions in Indonesia experienced problems in terms of late distribution of goods up to 15-20%, this would have a bad impact on the industry in the future, so to overcome the problems above the application of the ant colony optimization algorithm can help the above problems by placing 4 ants and the ants will spread from point A to point H. In the results of this study, there are 4 ants that move together where the best results are obtained by ant 2, closest to the point H, where the value obtained reaches 0,00015