Complex Optimization problems are solved effectively by heuristic approaches. Bio-inspired algorithms play a vital role in solving various complex computational problems. Ant Colony Optimization is one such bio-inspired techniques that stand even after three decades in addressing such issues. Travelling Salesman Problem is taken as a case study and an enhanced ant colony algorithm is used to solve it using the best feature of ACO called as pheromone. The proposed technique involves a modified pheromone rule plays a key parameter in solving the TSP. The experimental medium takes a graph of cities and their distances, followed by solving it using the proposed approach. The data analytics of maximum, mean and minimum costs of the graph are analyzed using R tool. The experimental results prove that the proposed enhanced ant colony algorithm effectively solves Travelling Salesman Problem.

Optimization, Travelling Salesman Problem, Bio-Inspired, Ant colony Algorithm, Pheromone

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