A Parallelized Multi-objective Particle Swarm Optimization Algorithm Based on MPI
GENG Wenjing1 , DONG Hongbin1, DING Rui1,2
1.College of Computer Science and Technology, Harbin Engineering University, Harbin 150001 2.School of Computer and Information Technology, Mudanjiang Normal University, Mudanjiang 157011
Abstract：To improve the efficiency and accuracy of speed-constrained multi-objective particle swarm optimization(SMPSO), a parallelized SMPSO algorithm based on Message Passing Interface(MPI)(M-SMPSO) is proposed. The master-slave mode of MPI is used in the proposed algorithm. The entire population is divided into several sub-populations. Then, these sub-populations are evolved independently. In addition, an adaptive global optimal solution selection strategy is proposed to balance the distribution and convergence. Several standard test functions are adopted to verify the performance of the proposed algorithm. The experimental results show that ompared with other multi-objective algorithms, M-SMPSO obtains a higher speedup ratio and it converges quickly.
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2018, Vol. 31 
