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Global Optimization of Nonconvex Polynomial Programming Problems Having Rational Exponents
Journal of Global Optimization, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Sufficient global optimality conditions for some nonconvex quadratic program problems
2010 Second International Conference on Communication Systems, Networks and Applications, 2010In this paper, a class of quadratic program problem with quadratic constrains is studied. Some sufficient global optimality conditions for some nonconvex quadratic program problems with quadratic constrains are presented according to the property of L- subdifferential.
null Jia Zhang, null Zhiyuan Tian
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RLT-Based Global Optimization Algorithms for Nonconvex Polynomial Programming Problems
1999Thus far, we have considered the generation of tight relaxations leading to the convex hull representation for linear and nonlinear (polynomial) discrete mixed-integer programming problems using the Reformulation-Linearization Technique (RLT). It turns out that because of its natural facility to enforce relationships between different polynomial terms,
Hanif D. Sherali, Warren P. Adams
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Journal of Global Optimization, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ramkumar Karuppiah, Ignacio E. Grossmann
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Ramkumar Karuppiah, Ignacio E. Grossmann
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Global optimization of a class of nonconvex quadratically constrained quadratic programming problems
Acta Mathematica Sinica, English Series, 2011zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Journal of Mechanical Design, 2009
We propose a deterministic approach for global optimization of nonconvex quasiseparable problems encountered frequently in engineering systems design. Our branch and bound-based optimization algorithm applies Lagrangian decomposition to (1) generate tight lower bounds by exploiting the structure of the problem and (2) enable parallel computing of ...
Aida Khajavirad, Jeremy J. Michalek
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We propose a deterministic approach for global optimization of nonconvex quasiseparable problems encountered frequently in engineering systems design. Our branch and bound-based optimization algorithm applies Lagrangian decomposition to (1) generate tight lower bounds by exploiting the structure of the problem and (2) enable parallel computing of ...
Aida Khajavirad, Jeremy J. Michalek
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Journal of Global Optimization
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Dillard Robertson +2 more
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Dillard Robertson +2 more
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IEEE Transactions on Cybernetics
A swarm-exploring neurodynamic network (SENN) based on a two-timescale model is proposed in this study for solving nonconvex nonlinear programming problems. First, by using a convergent-differential neural network (CDNN) as a local quadratic programming (QP) solver and combining it with a two-timescale model design method, a two-timescale convergent ...
Yamei Luo +5 more
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A swarm-exploring neurodynamic network (SENN) based on a two-timescale model is proposed in this study for solving nonconvex nonlinear programming problems. First, by using a convergent-differential neural network (CDNN) as a local quadratic programming (QP) solver and combining it with a two-timescale model design method, a two-timescale convergent ...
Yamei Luo +5 more
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INFORMS Journal on Computing
We learn optimal instance-specific heuristics for the global minimization of nonconvex quadratically constrained quadratic programs (QCQPs). Specifically, we consider partitioning-based convex mixed-integer programming relaxations for nonconvex QCQPs and propose the novel problem of strong partitioning to optimally partition variable domains without ...
Rohit Kannan +2 more
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We learn optimal instance-specific heuristics for the global minimization of nonconvex quadratically constrained quadratic programs (QCQPs). Specifically, we consider partitioning-based convex mixed-integer programming relaxations for nonconvex QCQPs and propose the novel problem of strong partitioning to optimally partition variable domains without ...
Rohit Kannan +2 more
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