A hybrid learning framework integrating chaotic Niche alpha evolution for student academic performance prediction. [PDF]
Sci RepChen H, Zhou Y, Cao Q.
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Higher-Order Thinking Skills Optimizer: A Metaheuristic Algorithm Inspired by Human Behavior and Its Application in Real-World Constrained Engineering Optimization Problems. [PDF]
Biomimetics (Basel)Han Z, Qiao Y, Fu H, Gao Y.
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De novo design of peptides localizing at the interface of biomolecular condensates
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Approximation of global optimal values of nonconvex programs using Successive Convex Relaxation Method (Continuous and Discrete Mathematics for Optimization)openaire
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A New Global Optimization Scheme for Quadratic Programs with Low-Rank Nonconvexity
INFORMS Journal on Computing, 2021We consider the classical convex constrained nonconvex quadratic programming problem where the Hessian matrix of the objective to be minimized has r negative eigenvalues, denoted by (QPr). Based on a biconvex programming reformulation in a slightly higher dimension, we propose a novel branch-and-bound algorithm to solve (QP1) and show that it returns ...
Xiaoli Cen, Yong Xia 0002
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Global optimization of nonconvex factorable programming problems
Mathematical Programming, 2001In this paper is presented a global optimization approach for solving a class of nonconvex factorable programming problems, that arise in a variety of engineering process control and design problems. McCormick introduced the nonconvex factorable programming problem in 1976 in a different, but equivalent, form.
Hanif D. Sherali, Hongjie Wang
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Global optimization of a rank-two nonconvex program
Mathematical Methods of Operations Research, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
CAMBINI, RICCARDO, SODINI, CLAUDIO
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A global optimization method for nonconvex separable programming problems
European Journal of Operational Research, 1999zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Han-Lin Li 0003, Chian-Son Yu
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Abstract A global optimization algorithm for nonconvex Generalized Disjunctive Programming (GDP) problems is proposed in this paper. By making use of convex underestimating functions for bilinear, linear fractional and concave separable functions in the continuous variables, the convex hull of each nonlinear disjunction is constructed.
Sangbum Lee, Ignacio E Grossmann
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On Global Linear Convergence in Stochastic Nonconvex Optimization for Semidefinite Programming
IEEE Transactions on Signal Processing, 2019Nonconvex reformulations via low-rank factorization for stochastic convex semidefinite optimization problem have attracted arising attention due to their empirical efficiency and scalability. Compared with the original convex formulations, the nonconvex ones typically involve much fewer variables, allowing them to scale to scenarios with millions of ...
Jinshan Zeng, Ke Ma 0001, Yuan Yao 0011
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