Bi-objective burn-in modeling and optimization

Zhi-Sheng Ye (), Loon-Ching Tang and Min Xie

Annals of Operations Research, 2014, vol. 212, issue 1, 214 pages

Abstract: This study develops a bi-objective method for burn-in decision makings with a view to achieving an optimal trade-off between the cost and the performance measures. Under the proposed method, a manufacturer specifies the relative importance between the cost and the performance measures. Then a single-objective optimal solution can be obtained through optimizing the weighted combination of these two measures. Based on this method, we build a specific model when the performance objective is the survival probability given a mission time. We prove that the optimal burn-in duration is decreasing in the weight assigned to the normalized cost. Then, we develop an algorithm to populate the Pareto frontier in case the manufacturer has no idea about the relative weight. Copyright Springer Science+Business Media New York 2014

Keywords: Cost-based burn-in; Performance-based burn-in; Pareto frontier (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1007/s10479-013-1419-z (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:212:y:2014:i:1:p:201-214:10.1007/s10479-013-1419-z

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-013-1419-z

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().