EconPapers    
Economics at your fingertips  
 

Branch-and-Reduction Algorithm for Indefinite Quadratic Programming Problem

Yongjian Qiu, Yuming Zhu, Jingben Yin and Zhihan Lv

Complexity, 2021, vol. 2021, 1-14

Abstract: This paper presents a rectangular branch-and-reduction algorithm for globally solving indefinite quadratic programming problem (IQPP), which has a wide application in engineering design and optimization. In this algorithm, first of all, we convert the IQPP into an equivalent bilinear optimization problem (EBOP). Next, a novel linearizing technique is presented for deriving the linear relaxation programs problem (LRPP) of the EBOP, which can be used to obtain the lower bound of the global optimal value to the EBOP. To obtain a global optimal solution of the EBOP, the main computational task of the proposed algorithm involves the solutions of a sequence of LRPP. Moreover, the global convergent property of the algorithm is proved, and numerical experiments demonstrate the higher computational performance of the algorithm.

Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/complexity/2021/5578427.pdf (application/pdf)
http://downloads.hindawi.com/journals/complexity/2021/5578427.xml (application/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:5578427

DOI: 10.1155/2021/5578427

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().

 
Page updated 2025-03-19
Handle: RePEc:hin:complx:5578427