dc.contributor | Universidade Federal de São Carlos (UFSCar) | |
dc.contributor | Universidade Estadual Paulista (Unesp) | |
dc.contributor | Universidade Estadual de Maringá (UEM) | |
dc.date.accessioned | 2021-06-25T10:11:50Z | |
dc.date.accessioned | 2022-12-19T22:02:20Z | |
dc.date.available | 2021-06-25T10:11:50Z | |
dc.date.available | 2022-12-19T22:02:20Z | |
dc.date.created | 2021-06-25T10:11:50Z | |
dc.date.issued | 2020-01-01 | |
dc.identifier | Brazilian Journal of Probability and Statistics, v. 34, n. 4, p. 712-727, 2020. | |
dc.identifier | 0103-0752 | |
dc.identifier | http://hdl.handle.net/11449/205221 | |
dc.identifier | 10.1214/19-BJPS453 | |
dc.identifier | 2-s2.0-85091579258 | |
dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5385819 | |
dc.description.abstract | Conducting sequencing experiments with good statistical properties and low cost is a crucial challenge for both researchers and practi-tioners. The main reason for this challenge is the combinatorial nature of the problem and the possible conflicts among objectives. The problem was addressed by proposing a mathematical programming formulation aimed at generating minimum-cost run orders with the best statistical properties for 2k full-factorial and fractional-factorial designs. The approach performance is evaluated using designs of up to 64 experiments with different levels of reso-lution. The results indicate that the approach can yield optimal or sub-optimal solutions, depending on the objectives established for a given design matrix. | |
dc.language | eng | |
dc.relation | Brazilian Journal of Probability and Statistics | |
dc.source | Scopus | |
dc.subject | Combinatorial optimization | |
dc.subject | Design of experiments | |
dc.subject | Linear time trend | |
dc.subject | Mathematical pro-gramming | |
dc.subject | Systematic sequencing | |
dc.title | Bi-objective mathematical model for optimal sequencing of two-level factorial designs | |
dc.type | Artículos de revistas | |