Implementation of a Parallel Algorithm Based on a Spark Cloud Computing Platform
AbstractParallel algorithms, such as the ant colony algorithm, take a long time when solving large-scale problems. In this paper, the MAX-MIN Ant System algorithm (MMAS) is parallelized to solve Traveling Salesman Problem (TSP) based on a Spark cloud computing platform. We combine MMAS with Spark MapReduce to execute the path building and the pheromone operation in a distributed computer cluster. To improve the precision of the solution, local optimization strategy 2-opt is adapted in MMAS. The experimental results show that Spark has a very great accelerating effect on the ant colony algorithm when the city scale of TSP or the number of ants is relatively large. View Full-Text
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Wang, L.; Wang, Y.; Xie, Y. Implementation of a Parallel Algorithm Based on a Spark Cloud Computing Platform. Algorithms 2015, 8, 407-414.
Wang L, Wang Y, Xie Y. Implementation of a Parallel Algorithm Based on a Spark Cloud Computing Platform. Algorithms. 2015; 8(3):407-414.Chicago/Turabian Style
Wang, Longhui; Wang, Yong; Xie, Yudong. 2015. "Implementation of a Parallel Algorithm Based on a Spark Cloud Computing Platform." Algorithms 8, no. 3: 407-414.