Novel Applications of Ant Colony Optimization with the Traveling Salesman Problem in DNA Sequence Optimization

Abstract

The Ant Colony Optimization Algorithm is a novel optimization algorithm based on the intelligence of ant behavior, whereas the Traveling Salesman Problem is the problem of determining the shortest route between a group of cities that start in one city and visit each other city only once before returning to the starting (home) city. This study proposes an Ant Colony Optimization approach with the Traveling Salesman Problem (ACO-TSP) for DNA Sequence Optimizations. The proposed technique is a unique ant colony optimization approach for reconstructing DNA sequences from fragments of DNA. Existing meta-heuristics, on the other hand, are consistently outperformed in terms of performance by newly invented constructive heuristics. This model was developed based on these novel heuristics, with four nodes (cities) representing the four DNA bases. According to the findings of the experiments, the new approach is more reliable and generates higher-quality results.