A new branch and bound algorithm for minimax ratios problems

• Autorzy: Yingfeng Zhao , Sanyang Liu , Hongwei Jiao
• Języki publikacji: EN

Abstrakty

EN

This study presents an efficient branch and bound algorithm for globally solving the minimax fractional programming problem (MFP). By introducing an auxiliary variable, an equivalent problem is firstly constructed and the convex relaxation programming problem is then established by utilizing convexity and concavity of functions in the problem. Other than usual branch and bound algorithm, an adapted partition skill and a practical reduction technique performed only in an unidimensional interval are incorporated into the algorithm scheme to significantly improve the computational performance. The global convergence is proved. Finally, some comparative experiments and a randomized numerical test are carried out to demonstrate the efficiency and robustness of the proposed algorithm.

Słowa kluczowe

EN

Fractional programming; Global optimization; Branch and bound; Adapted ratio partition

Kategorie tematyczne

• 90C30: Nonlinear programming
• 90C26: Nonconvex programming, global optimization

• Wydawca: De Gruyter Open
• Czasopismo: Open Mathematics
• Rocznik: 2017
• Tom: 15
• Numer: 1
• Strony: 840-851

Daty

wydano

2017-01-01

otrzymano

2016-12-05

zaakceptowano

2017-04-03

online

2017-06-22

Twórcy

autor

Yingfeng Zhao

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autor

Sanyang Liu

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autor

Hongwei Jiao

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Identyfikatory

DOI

10.1515/math-2017-0072