Hybrid Local Search Algorithm for Optimization Route of Travelling Salesman Problem

This study explores the Traveling Salesman Problem (TSP) in Medan City, North Sumatra, Indonesia, analyzing 100 geographical locations for the shortest route determination. Four heuristic algorithms—Nearest Neighbor (NN), Repetitive Nearest Neighbor (RNN), Hybrid NN, and Hybrid RNN—are investigated using RStudio software and benchmarked against various problem instances and TSPLIB data. The results reveal that algorithm performance is contingent on problem size and complexity, with hybrid methods showing promise in producing superior solutions. Statistical analysis confirms the significance of the differences between non-hybrid and hybrid methods, emphasizing the potential for hybridization to enhance solution quality. This research advances our understanding of heuristic algorithm performance in TSP problem-solving and underscores the transformative potential of hybridization strategies in optimization.

@article{Zuhanda2023,
  title     = {Hybrid Local Search Algorithm for Optimization Route of Travelling Salesman Problem},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {9},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Muhammad Khahfi Zuhanda and Noriszura Ismail and Rezzy Eko Caraka and Rahmad Syah and Prana Ugiana Gio},
  doi       = {10.14569/IJACSA.2023.0140935},
  url       = {https://doi.org/10.14569/IJACSA.2023.0140935}
}