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- Title
Efficient algorithm for globally computing the min–max linear fractional programming problem.
- Authors
Jiao, Hongwei; Wang, Wenjie; Ge, Li; Shen, Peiping; Shang, Youlin
- Abstract
In this paper, we consider the min–max linear fractional programming problem (MLFP) which is NP-hard. We first introduce some auxiliary variables to derive an equivalent problem of the problem (MLFP). An outer space branch-and-bound algorithm is then designed by integrating some basic operations such as the linear relaxation method and branching rule. The global convergence of the proposed algorithm is proved by means of the subsequent solutions of a series of linear relaxation programming problems, and the computational complexity of the proposed algorithm is estimated based on the branching rule. Finally, numerical experimental results demonstrate the proposed algorithm can be used to efficiently compute the globally optimal solutions of test examples.
- Subjects
FRACTIONAL programming; ALGORITHMS; OUTER space; COMPUTATIONAL complexity; RELAXATION methods (Mathematics); GLOBAL optimization; LINEAR programming
- Publication
RAIRO: Operations Research (2804-7303), 2023, Vol 57, Issue 3, p1523
- ISSN
2804-7303
- Publication type
Article
- DOI
10.1051/ro/2023075