A potential practical algorithm for minimizing the sum of affine fractional functions

This article presents and validates a potential practical algorithm for minimizing the sum of affine fractional functions over a polyhedron. During the branch and bound search, this algorithm computes the lower bounds by solving the affine relaxation problems of the equivalent problem, which are der...

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Bibliographic Details
Published inOptimization Vol. 72; no. 6; pp. 1577 - 1607
Main Authors Jiao, Hongwei, Shang, Youlin, Chen, Rongjiang
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 03.06.2023
Taylor & Francis LLC
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Summary:This article presents and validates a potential practical algorithm for minimizing the sum of affine fractional functions over a polyhedron. During the branch and bound search, this algorithm computes the lower bounds by solving the affine relaxation problems of the equivalent problem, which are derived by utilizing a two-level affine relaxation technique. By successive refinement and successively solving a series of affine relaxation problems, the algorithm is convergent to the global minimum of the primal problem. Moreover, the gap between the objective function and its affine relaxation function is derived for the first time, and when the partition interval tends to be infinitesimal, the gap is infinitely close to zero. Furthermore, the maximum iterations of the proposed algorithm are derived by estimating its computational complexity. Some test problems are solved to verify the potential practical and computational advantages of the algorithm.
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content type line 14
ISSN:0233-1934
1029-4945
DOI:10.1080/02331934.2022.2032051