A new deterministic global computing algorithm for solving a kind of linear fractional programming

This paper investigates a class of linear fractional programming (LFP) problem, which minimizes the sum of a finite number of linear fractional functions over a polyhedral region. Firstly, the equivalence problem (EP) of the LFP problem is given by a new two-stage transformation method. Secondly, co...

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Vydáno v:	Optimization Ročník 72; číslo 6; s. 1485 - 1513
Hlavní autoři:	Zhang, Bo, Gao, YueLin, Liu, Xia, Huang, XiaoLi
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Philadelphia Taylor & Francis 03.06.2023 Taylor & Francis LLC
Témata:	Algorithms branch and bound Global optimization linear fractional programming Mathematical programming Optimization output-space
ISSN:	0233-1934, 1029-4945
On-line přístup:	Získat plný text
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Popis
Shrnutí:	This paper investigates a class of linear fractional programming (LFP) problem, which minimizes the sum of a finite number of linear fractional functions over a polyhedral region. Firstly, the equivalence problem (EP) of the LFP problem is given by a new two-stage transformation method. Secondly, considering the characteristics that the branch-and-bound algorithm can guarantee the global optimality of the solution to an optimization problem, and then based on the EP, we discuss the bounding operation, branching operation, pruning operation and rectangle-region reduction technique of this algorithm. After that, the convergence of the algorithm is proved and its computational complexity is deduced from the worst case. Finally, some experiments are reported to verify the effectiveness, feasibility and other performance of the proposed algorithm.
Bibliografie:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14
ISSN:	0233-1934 1029-4945
DOI:	10.1080/02331934.2022.2027940