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Parallelization of Generic PSO Java Code Using MPJExpress

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dc.description.abstract Many scientific, engineering and economic problems involve the optimization of a set of parameters. The Particle Swarm Optimization (PSO) is one of the new techniques that have been empirically shown to perform well. The PSO algorithm is a population-based search algorithm based on simulating the social behavior of birds within a flock. Large-scale engineering optimization problems impose large computational demands, resulting in long solution times even on modern high-end processors. To obtain enhanced computational throughput and global search capability parallel algorithms and parallel architectures have drawn lots of attention. Parallelization of PSO has proved to enhance computational throughput and global search capability In this paper, we detail the parallelization of an increasingly popular global search method, the PSO algorithm using MPJ Express. Both synchronous and asynchronous parallel implementations are investigated. The parallel PSO algorithm’s robustness and efficiency are demonstrated by using four standard benchmark functions Alpine, Rosenbrock, Rastrigin and Schaffer. en_US
dc.title Parallelization of Generic PSO Java Code Using MPJExpress en_US
dc.date.accessioned 2013-02-21T20:48:33Z
dc.date.available 2013-02-21T20:48:33Z
dc.date.issued 2013-02-21
dc.identifier.uri http://hdl.handle.net/10365/22571
dc.thesis.degree Paper (M.S.)--North Dakota State University, 2013. en_US
dc.contributor.advisor Ludwig, Simone
dc.subject.lcsh Parallel algorithms. en_US
dc.subject.lcsh Swarm intelligence. en_US
dc.subject.lcsh Mathematical optimization.
dc.creator.author Madamanchi, Manoj Babu
dc.degree.departmentCollege Master of Science / Computer Science, College of Science and Mathematics, 2013.
dc.date.created 2013

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