An eigenvalue decomposition based branch-and-bound algorithm for nonconvex quadratic programming problems with convex quadratic constraints
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Publication:513160
DOI10.1007/s10898-016-0436-2zbMath1366.90171OpenAlexW2346374866MaRDI QIDQ513160
Cheng Lu, Zhi-bin Deng, Qing-Wei Jin
Publication date: 3 March 2017
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10898-016-0436-2
Polyhedral combinatorics, branch-and-bound, branch-and-cut (90C57) Nonconvex programming, global optimization (90C26) Quadratic programming (90C20)
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Uses Software
Cites Work
- A Lagrangian-DNN relaxation: a fast method for computing tight lower bounds for a class of quadratic optimization problems
- Semidefinite relaxations for non-convex quadratic mixed-integer programming
- Copositive optimization -- recent developments and applications
- Trust-region problems with linear inequality constraints: exact SDP relaxation, global optimality and robust optimization
- Semidefinite relaxations for quadratically constrained quadratic programming: A review and comparisons
- New and old bounds for standard quadratic optimization: dominance, equivalence and incomparability
- Optimizing a polyhedral-semidefinite relaxation of completely positive programs
- Semidefinite programming versus the reformulation-linearization technique for nonconvex quadratically constrained quadratic programming
- Applications of second-order cone programming
- Quadratic programming with one negative eigenvalue is NP-hard
- Globally solving nonconvex quadratic programming problems via completely positive programming
- A polyhedral study of nonconvex quadratic programs with box constraints
- A branch-and-cut algorithm for nonconvex quadratic programs with box constraints
- A polyhedral branch-and-cut approach to global optimization
- A simplicial branch-and-bound algorithm for solving quadratically constrained quadratic programs
- Conic approximation to nonconvex quadratic programming with convex quadratic constraints
- Narrowing the difficulty gap for the Celis-Dennis-Tapia problem
- Detecting copositivity of a symmetric matrix by an adaptive ellipsoid-based approximation scheme
- On the copositive representation of binary and continuous nonconvex quadratic programs
- A finite branch-and-bound algorithm for nonconvex quadratic programming via semidefinite relaxations
- Convex relaxations of non-convex mixed integer quadratically constrained programs: Extended formulations
- Computational aspects of a branch and bound algorithm for quadratic zero- one programming
- A Hierarchy of Relaxations between the Continuous and Convex Hull Representations for Zero-One Programming Problems
- KKT Solution and Conic Relaxation for Solving Quadratically Constrained Quadratic Programming Problems
- Semidefinite Relaxation Bounds for Indefinite Homogeneous Quadratic Optimization
- Class of global minimum bounds of polynomial functions
- Using SeDuMi 1.02, A Matlab toolbox for optimization over symmetric cones
- The trust region subproblem and semidefinite programming*
- Adaptive computable approximation to cones of nonnegative quadratic functions
- A Quadratically Constrained Quadratic Optimization Model for Completely Positive Cone Programming
- Approximation Bounds for Quadratic Optimization with Homogeneous Quadratic Constraints
- Copositive Relaxation Beats Lagrangian Dual Bounds in Quadratically and Linearly Constrained Quadratic Optimization Problems
- On Cones of Nonnegative Quadratic Functions
- On copositive programming and standard quadratic optimization problems
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