@article{oai:ptu.repo.nii.ac.jp:00000048,
 author = {印南　, 信男 and Innami, Michio},
 issue = {1},
 journal = {技能科学研究},
 month = {},
 note = {Particle Swarm Optimization (PSO) is one of the population
based metaheuristics. The algorithm is simple yet the
convergence is rather fast. The parameter values have a large influence on the search performance. Many studies on
PSO parameter tuning have been conducted so far. This paper proposes determining parameters separately in eac h
stage into which the iterative process is divided, using Design of Experiments (DoE) methodology. The situation of
the swarm is considered to be changing as the process proceeds. Hence, a certain effect is expected with this
method. The exploration with the proposed method is performed on four test functions. Additionally the exploration
with three other methods is also conducted for comparison. The proposed method yields good results. This study
also reveals that the search performance improves when para meters, such as inertia weight, increase as the process
proceeds.},
 pages = {36--42},
 title = {【論文】Optimization of PSO by Determining Parameters for Multiple Stages with DoE},
 volume = {35},
 year = {2019}
}