Journal
APPLICABLE ANALYSIS
Volume 100, Issue 15, Pages 3199-3211Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00036811.2020.1712373
Keywords
Linear fractional vector optimization; efficient solution; Geoffrion's properly efficient solution; coincidence of solution sets; recession cone
Categories
Funding
- National Foundation for Science & Technology Development (Vietnam) [101.01-2018.306]
- Le Quy Don Technical University (Vietnam), China Medical University (Taiwan)
- Institute of Mathematics (VAST, Vietnam)
Ask authors/readers for more resources
This paper introduces two new theorems on Geoffrion's properly efficient solutions and provides seven examples demonstrating their applications in linear fractional vector optimization problems with unbounded constraint sets. The first theorem gives sufficient conditions for the efficient solution set to coincide with Geoffrion's properly efficient solution set when all components of the objective function are properly fractional. The second theorem establishes sufficient conditions for an efficient solution to be a Geoffrion's properly efficient solution, even when the objective function includes some affine components.
This paper presents two new theorems on Geoffrion's properly efficient solutions and seven examples illustrating their applications to linear fractional vector optimization problems with unbounded constraint sets. Provided that all the components of the objective function are properly fractional, the first theorem gives sufficient conditions for the efficient solution set to coincide with the Geoffrion properly efficient solution set. Admitting that the objective function can have some affine components, in the second theorem we give sufficient conditions for an efficient solution to be a Geoffrion's properly efficient solution. The recession cone of the constraint set, the derivatives of the scalar objective functions, but no tangent cone to the constraint set at the efficient point, are used in the second theorem.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available