Optimizing a linear fractional function over the integer efficient set
Wassila Drici (),
Fatma Zohra Ouail () and
Mustapha Moulai ()
Additional contact information
Wassila Drici: USTHB
Fatma Zohra Ouail: USTHB
Annals of Operations Research, 2018, vol. 267, issue 1, No 8, 135-151
Abstract:
Abstract In this article, a new exact method is proposed to solve a problem, say $$(ILFP)_E$$ ( I L F P ) E , of maximizing a linear fractional function over the integer efficient set of multi-objective integer linear programming problem (MOILP). The method is developed through the branch and cut technique and the continuous linear fractional programming, to come up with an integer optimal solution for problem $$(ILFP)_E$$ ( I L F P ) E without having to explicitly list all efficient solutions of problem (MOILP). The branching process is strengthened by an efficient cut as well as an efficiency test so that a large number of non-efficient feasible solutions can be avoided. Illustrative example and an experimental study are reported to show the merit of this new approach.
Keywords: Multi-objective programming; Integer programming; Linear fractional programming; Branch and cut; 90C29; 90C10; 90C32; 90C57 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10479-017-2691-0 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:267:y:2018:i:1:d:10.1007_s10479-017-2691-0
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479
DOI: 10.1007/s10479-017-2691-0
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 ().