Parallel algorithms, such as the ant colony algorithm, take a long time when\nsolving large-scale problems. In this paper, the MAX-MIN Ant System algorithm (MMAS)\nis parallelized to solve Traveling Salesman Problem (TSP) based on a Spark cloud\ncomputing platform. We combine MMAS with Spark MapReduce to execute the path\nbuilding and the pheromone operation in a distributed computer cluster. To improve the\nprecision of the solution, local optimization strategy 2-opt is adapted in MMAS. The\nexperimental results show that Spark has a very great accelerating effect on the ant colony\nalgorithm when the city scale of TSP or the number of ants is relatively large.
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