TY - JOUR
T1 - A modified Particle Swarm Optimization technique for finding optimal designs for mixture models
AU - Wong, Weng Kee
AU - Chen, Ray Bing
AU - Huang, Chien Chih
AU - Wang, Weichung
N1 - Publisher Copyright:
© 2015 Wong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2015/6/19
Y1 - 2015/6/19
N2 - Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and without constraints on the components, and also for related models, like the log contrast models. We also compare the modified PSO performance with Fedorov's algorithm, a popular algorithm used to generate optimal designs, Cocktail algorithm, and the recent algorithm proposed by [1].
AB - Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and without constraints on the components, and also for related models, like the log contrast models. We also compare the modified PSO performance with Fedorov's algorithm, a popular algorithm used to generate optimal designs, Cocktail algorithm, and the recent algorithm proposed by [1].
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U2 - 10.1371/journal.pone.0124720
DO - 10.1371/journal.pone.0124720
M3 - Article
C2 - 26091237
AN - SCOPUS:84938926490
VL - 10
JO - PLoS One
JF - PLoS One
SN - 1932-6203
IS - 6
M1 - e0124720
ER -