A modified Particle Swarm Optimization technique for finding optimal designs for mixture models

Weng Kee Wong; Ray Bing Chen; Chien Chih Huang; Weichung Wang

doi:10.1371/journal.pone.0124720

A modified Particle Swarm Optimization technique for finding optimal designs for mixture models

Weng Kee Wong, Ray Bing Chen, Chien Chih Huang, Weichung Wang

數據科學研究所

研究成果: Article › 同行評審

22 引文斯高帕斯（Scopus）

摘要

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].

原文	English
文章編號	e0124720
期刊	PloS one
卷	10
發行號	6
DOIs	https://doi.org/10.1371/journal.pone.0124720
出版狀態	Published - 2015 六月 19

All Science Journal Classification (ASJC) codes

Biochemistry, Genetics and Molecular Biology(all)
Agricultural and Biological Sciences(all)
General

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10.1371/journal.pone.0124720

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