# Branch-delete-bound algorithm for globally solving quadratically constrained quadratic programs

Zhisong Hou; Hongwei Jiao; Lei Cai; Chunyang Bai

Open Mathematics (2017)

- Volume: 15, Issue: 1, page 1212-1224
- ISSN: 2391-5455

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topZhisong Hou, et al. "Branch-delete-bound algorithm for globally solving quadratically constrained quadratic programs." Open Mathematics 15.1 (2017): 1212-1224. <http://eudml.org/doc/288510>.

@article{ZhisongHou2017,

abstract = {This paper presents a branch-delete-bound algorithm for effectively solving the global minimum of quadratically constrained quadratic programs problem, which may be nonconvex. By utilizing the characteristics of quadratic function, we construct a new linearizing method, so that the quadratically constrained quadratic programs problem can be converted into a linear relaxed programs problem. Moreover, the established linear relaxed programs problem is embedded within a branch-and-bound framework without introducing any new variables and constrained functions, which can be easily solved by any effective linear programs algorithms. By subsequently solving a series of linear relaxed programs problems, the proposed algorithm can converge the global minimum of the initial quadratically constrained quadratic programs problem. Compared with the known methods, numerical results demonstrate that the proposed method has higher computational efficiency.},

author = {Zhisong Hou, Hongwei Jiao, Lei Cai, Chunyang Bai},

journal = {Open Mathematics},

keywords = {Quadratically constrained quadratic programs; Global optimization; Linearizing method; Deleting technique; Branch-delete-bound algorithm},

language = {eng},

number = {1},

pages = {1212-1224},

title = {Branch-delete-bound algorithm for globally solving quadratically constrained quadratic programs},

url = {http://eudml.org/doc/288510},

volume = {15},

year = {2017},

}

TY - JOUR

AU - Zhisong Hou

AU - Hongwei Jiao

AU - Lei Cai

AU - Chunyang Bai

TI - Branch-delete-bound algorithm for globally solving quadratically constrained quadratic programs

JO - Open Mathematics

PY - 2017

VL - 15

IS - 1

SP - 1212

EP - 1224

AB - This paper presents a branch-delete-bound algorithm for effectively solving the global minimum of quadratically constrained quadratic programs problem, which may be nonconvex. By utilizing the characteristics of quadratic function, we construct a new linearizing method, so that the quadratically constrained quadratic programs problem can be converted into a linear relaxed programs problem. Moreover, the established linear relaxed programs problem is embedded within a branch-and-bound framework without introducing any new variables and constrained functions, which can be easily solved by any effective linear programs algorithms. By subsequently solving a series of linear relaxed programs problems, the proposed algorithm can converge the global minimum of the initial quadratically constrained quadratic programs problem. Compared with the known methods, numerical results demonstrate that the proposed method has higher computational efficiency.

LA - eng

KW - Quadratically constrained quadratic programs; Global optimization; Linearizing method; Deleting technique; Branch-delete-bound algorithm

UR - http://eudml.org/doc/288510

ER -

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