Study of The Ant Colony With Its Application to The Traveling Salesman Problem
Keywords:
ACO, Colony Optimization, pheromone trail, Swarm Intelligence, Traveling SalesmanAbstract
Ant Colony Optimization (ACO) is one of the most known nature inspired metheuristic techniques, which is basically based on the simulation of the social behaviour of ants when searching for the shortest paths between their colony and their food source. The algorithm was originally introduced in 1992 by Marco Dorigo to solve NP-hard combinatorial optimization problems which are hard to solve with traditional algorithms because of their large search space and high computational complexity. The research shows that the ant algorithm is a flexible yet powerful mathematical model that can adapt to changes occurring in dynamically changing complex systems, and that new opportunities for hybridizing with techniques of artificial intelligence/machine learning emerge for further increasing the convergence speed and the efficiency of the system. It has been used to solve the travelling salesman problem and has proved to be successful.
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