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A Hybrid Mechanism of Particle Swarm Optimization and Differential Evolution Algorithms based on Spark
2019
KSII Transactions on Internet and Information Systems
With the onset of the big data age, data is growing exponentially, and the issue of how to optimize large-scale data processing is especially significant. Large-scale global optimization (LSGO) is a research topic with great interest in academia and industry. Spark is a popular cloud computing framework that can cluster large-scale data, and it can effectively support the functions of iterative calculation through resilient distributed datasets (RDD). In this paper, we propose a hybrid
doi:10.3837/tiis.2019.12.010
fatcat:r7s2xplblraqrj6jdnboeg33c4