Parallel PSO using MapReduce
- 1 September 2007
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 4 (1089778X), 7-14
- https://doi.org/10.1109/cec.2007.4424448
Abstract
In optimization problems involving large amounts of data, such as web content, commercial transaction information, or bioinformatics data, individual function evaluations may take minutes or even hours. particle swarm optimization (PSO) must be parallelized for such functions. However, large-scale parallel programs must communicate efficiently, balance work across all processors, and address problems such as failed nodes. We present mapreduce particle swarm optimization (MRPSO), a PSO implementation based on the mapreduce parallel programming model. We describe MapReduce and show how PSO can be naturally expressed in this model, without explicitly addressing any of the details of parallelization. We present a benchmark function for evaluating MRPSO and note that MRPSO is not appropriate for optimizing easily evaluated functions. We demonstrate that MRPSO scales to 256 processors on moderately difficult problems and tolerates node failures.Keywords
This publication has 8 references indexed in Scilit:
- Particle swarm optimizationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2014
- Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous EvaluationsJournal of Aerospace Information Systems, 2006
- Parallel asynchronous particle swarm optimizationInternational Journal for Numerical Methods in Engineering, 2006
- Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designsIEEE Transactions on Antennas and Propagation, 2005
- Parallel global optimization with the particle swarm algorithmInternational Journal for Numerical Methods in Engineering, 2004
- Small worlds and mega-minds: effects of neighborhood topology on particle swarm performancePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- The particle swarm - explosion, stability, and convergence in a multidimensional complex spaceIEEE Transactions on Evolutionary Computation, 2002
- Neural Networks for Pattern RecognitionPublished by Oxford University Press (OUP) ,1995