ANT COLONY OPTIMIZATION ALGORITHM AND ITS USE IN LOGISTICS AND BIOMEDICAL DIAGNOSTICS
Scientists often use algorithms in their research activities. This article describes the ant algorithm and its practical application to business, logistics and medicine. The purpose of the study is to demonstrate the use of an ant algorithm utilizing the computer code in the PYTHON programming language. The relevance of the study is to optimize both the Travelling Salesman Problem (TSP) and MRI diagnostics. The method of comparing the traditional approach with the ant algorithm optimization techniques to solve both the TSP and MRI diagnostics was used in the study. The graph with a number of cities was to analyze the distance between two cities. The table was made with the numbers of distances needed to find the shortest path. The results of our work is to developed programme code by using the ant algorithm in the PYTHON programming language. In conclusion, it is noted that the ant algorithm allows finding optimal solutions quickly. This makes the work of both a logistician and a diagnostician efficient. It is also less time and energy consuming.