Open Access Open Access  Restricted Access Subscription or Fee Access

GPU-Based Parallel Multi-objective Particle Swarm Optimization

You Zhou, Ying Tan


In the recent years, multi-objective particle swarm optimization (MOPSO) has become quite popular in the field of multi-objective optimization. However, due to a large amount of fitness evaluations as well as the task of archive maintaining, the running time of MOPSO for optimizing some difficult problems may be quite long. This paper proposes a parallel MOPSO based on consumer-level Graphics Processing Units (GPU), which, to our knowledge, is the first approach of optimizing multi-objective problems via PSO on the platform of GPU. Experiments on 4 two-objective benchmark test functions are conducted. Compared with the CPU based sequential MOPSO, our GPU based parallel MOPSO is much more efficient in terms of running time, and the speedups range from 3:74 to 7:92 times. When the problem is large-scale, i.e. the dimension of the decision vector is large, the speedups can be bigger than 10 times. Furthermore, the experimental results show that the larger the size of the swarm is, the more nondominated solutions are found, the higher the quality of solutions are, and the bigger the speedup is.


MOPSO, GPU, Parallel, Speedup.

Full Text:



  • There are currently no refbacks.

Disclaimer/Regarding indexing issue:

We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.