The Phasmatodea population evolution algorithm (ppe) is a relatively new swarm intelligence algorithm at present. A PSO algorithm with a parallel communication strategy can largely optimize the advantages of PSO and o...
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ISBN:
(纸本)9789811910579;9789811910562
The Phasmatodea population evolution algorithm (ppe) is a relatively new swarm intelligence algorithm at present. A PSO algorithm with a parallel communication strategy can largely optimize the advantages of PSO and overcome some of its shortcomings. Combining ppe and parallel particle swarm optimization, this paper proposes a parallel Phasmatodea population evolution algorithm (Pppe) with communication strategy. In this thesis, all populations are grouped to communicate and compete. This approach can change the location and number of populations and thus expand the search for populations on a global scale. Inspired by parallel PSO, the authors propose two exchange strategies in this paper. The first communication strategy is modelled on the first communication style of parallel PSO. The second communication strategy is modelled on the third communication style of parallel PSO. The algorithm was tested and analysed on 30 benchmark functions. The test results indicate that, under the same conditions, the improved algorithm outperforms the best fit and degree of convergence obtained by other similar algorithms.
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