- Referenced in 2583 articles
- linearly or quadratically constrained optimization problems where the objective to be optimized can be expressed ... linear function or a convex quadratic function. The variables in the model may be declared...
- Referenced in 720 articles
- number of standard problem types, including linear and quadratic programs (LPs/QPs), second-order cone programs ... also solve much more complex convex optimization problems, including many involving nondifferentiable functions, such...
- Referenced in 179 articles
- solving linear, quadratic, and nonlinear smooth optimization problems, both convex and nonconvex. It is also...
- Referenced in 937 articles
- MATLAB toolbox for rapid prototyping of optimization problems. The package initially aimed at the control ... linear programming, quadratic programming, second order cone programming, semidefinite programming, non-convex semidefinite programming, mixed...
- Referenced in 300 articles
- Nonlinear (convex & nonconvex/Global), Quadratic, Quadratically Constrained, Second Order Cone, Stochastic, and Integer optimization models faster ... expressing optimization models, a full featured environment for building and editing problems...
- Referenced in 26 articles
- methods one solves convex optimization problems, typically quadratic programs. Least Squares Support Vector Machines...
- Referenced in 44 articles
- algorithms for the solution of large optimization problems on high-performance parallel architectures. Our case ... convex quadratic problems. Our implementation of the GPCG algorithm within the Toolkit for Advanced Optimization...
- Referenced in 71 articles
- Major applications of mixed-integer quadratically-constrained quadratic programs (MIQCQP) include quality blending in process ... optimization in finance. Specific instantiations of MIQCQP in process networks optimization problems include: pooling problems ... production. Computational geometry problems formulated as MIQCQP include: point packing, cutting convex shapes from rectangles...
- Referenced in 5 articles
- hard subclass of non-convex quadratically-constrained optimization problems that commonly arises in process systems...
- Referenced in 39 articles
- high level description of a convex optimization problem family, and automatically generates custom C code ... problem family. The current implementation targets problem families that can be transformed, using disciplined convex ... programming techniques, to convex quadratic programs of modest size. CVXGEN generates simple, flat, library-free...
- Referenced in 3 articles
- canonical form as a convex optimization problem with quadratic constraints, in terms of discrete variables...
- Referenced in 39 articles
- functions for multiextremal multidimensional box-constrained global optimization is presented. Each test class consists ... functions are generated by defining a convex quadratic function systematically distorted by polynomials in order ... user defines the following parameters: (i) problem dimension, (ii) number of local minima, (iii) value...
- Referenced in 49 articles
- analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written ... book underscores the purpose of optimization: to solve practical problems on a computer. Accordingly...
- Referenced in 46 articles
- simple algebraic structure. The explicit subproblems are convex and separable, and they can be solved ... this paper, a special purpose dual optimizer is proposed to solve the explicit subproblem generated ... primary dual problem is itself replaced with a sequence of approximate quadratic subproblems with...
- Referenced in 5 articles
- primal-dual method for large scale convex quadratic programming In 1992 we prepared HOPDM ... optimization. We broadened this software subsequently to use it for a quadratic programming problem generated ... convex quadratic objectives.par Now we are presenting QHOPDM, a library for convex quadratic optimization with...
- Referenced in 40 articles
- linear (LPs), quadratic (QPs), and quadratically-constrained quadratic programs (QCQPs). ECOS also supports a small ... sparse) problem data. As a consequence, it can be used to solve optimization problems ... efficient standard algorithm for solving convex optimization problems. It uses regularization and iterative refinement techniques...
- Referenced in 15 articles
- scale, sparse, nonlinear optimization problems with millions of variables and constraints. Convexity is not required ... core foundations as a sparse sequential quadratic programming (SQP) / interior-point (IP) method; it includes ... development philosophy. Two large-scale optimization problems from space applications that demonstrate the robustness...
- Referenced in 34 articles
- unstable, but numerical testing on some difficult problems indicates that both implementations give excellent accuracy ... subroutine [”ZQPCVX: a Fortran subroutine for convex, quadratic programming”, Report DAMTP/1983/NA17, Dept. Appl. Math. Theor ... subroutine is compared with two widely available quadratic programming subroutines that employ feasible point methods ... Fortran package for quadratic programming”, Report SOL 83-7, Systems Optim. Lab., Rept. Oper...
- Referenced in 13 articles
- quadratic programming solver targeted at block-banded convex QPs that arise in optimal control, dynamic ... optimization, and estimation. The acronym DUNES stands for dual Newton strategy, the novel solution methodology ... data storage formats to better exploit the problem intrinsic structures. Problems...
- Referenced in 20 articles
- MPEC, that is an optimization problem whose objective function is quadratic, first-level constraints ... first and second level, ill-conditioning, convexity of the objective, monotonicity and symmetry...