Solving TSP Using Various Meta-Heuristic Algorithms
Real world problems like Travelling Salesman Problem (TSP) belong to NP-hard optimization problems which are difficult to solve using classical mathematical methods. Therefore, many alternate solutions have been developed to find the optimal solution in shortest possible time. Nature-inspired algorithms are one of the proposed solutions which are successful in finding the solutions that are very near to the optimal. In this paper, Classical TSP (CTSP) along with its variant Random TSP (RTSP) are solved using various meta-heuristic algorithms and their performance is compared on the basis of tour length. Results show that the Nature-inspired algorithms outperform both Traditional and Evolutionary algorithms and obtain optimal solutions.
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