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The Traveling Salesman (TSP) problem is one of the most common basic problems in the nondeterministic polynomial problems (NP-hard) category. TSP is a good combinatorial optimization problem where the salesman starts traveling in a randomly chosen city and then visits all other cities before returning to the original departure city. Since this belongs to an NP problem, no polynomial-time solution is available. Generating an optimal solution from TSP is therefore a difficult task, so a meta-heuristic approach may lead to a satisfying solution that solves TSP complexity. In this article, we propose a Spotted Hyena Optimizer (SHO) algorithm based on the MapReduce distributed computing framework (MH-SHO) for solving TSP. MapReduce is not suitable for iterative programs as its performance can be impacted by frequent disk I/O operations. Therefore, SHO combines Hadoop MapReduce to perform optimal path …