• CMA-ES

• Referenced in 100 articles [sw05063]
• free methods for numerical optimization of non-linear or non-convex continuous optimization problems. They...

• YALMIP

• Referenced in 868 articles [sw04595]
• free MATLAB toolbox for rapid prototyping of optimization problems. The package initially aimed ... second order cone programming, semidefinite programming, non-convex semidefinite programming, mixed integer programming, multi-parametric...

• MIForests

• Referenced in 6 articles [sw22587]
• random variables. These random variables are optimized by training random forests and using a fast ... iterative homotopy method for solving the non-convex optimization problem. Additionally, most previously proposed...

• RPSALG

• Referenced in 5 articles [sw12637]
• optimization problems: the first one consists of obtaining an approximate solution of some discretized convex ... second one requires to solve a non-convex optimization problem involving the parametric constraints...

• bilevel

• Referenced in 1 article [sw25305]
• optimality conditions. MPCCs are single-level non-convex optimization problems that do not satisfy...

• NCVX

• Referenced in 3 articles [sw24075]
• from a non-convex set. The heuristics, which employ convex relaxations, convex restrictions, local neighbour ... solution of a modest number of convex problems, and are meant to apply to general ... solving convex optimization problems. We study several examples of well known non-convex problems...

• LRIPy

• Referenced in 1 article [sw26565]
• Rank Constrained Optimization by Low-Rank Inducing Norms and Non-Convex Proximal Splitting Methods. Python ... rank optimization by Low-Rank Inducing Norms as well as non-convex Douglas-Rachford. Purpose...

• ASPIRE

• Referenced in 1 article [sw32496]
• science, such as computerized tomography, optimization (convex and non-convex), random matrix theory, signal...

• bmrm

• Referenced in 18 articles [sw11016]
• methods for minimization of convex and non-convex risk under L1 or L2 regularization. Implements ... linear SVM, multi-class SVM, f-beta optimization, ROC optimization, ordinal regression, quantile regression, epsilon...

• libcmaes

• Referenced in 1 article [sw28976]
• family for optimization of nonlinear non-convex ’blackbox’ functions. The implemented algorithms have a wide ... various disciplines, ranging from pure function minimization, optimization in industrial and scientific applications...

• LRINorm

• Referenced in 1 article [sw26564]
• Rank Constrained Optimization by Low-Rank Inducing Norms and Non-Convex Proximal Splitting Methods...

• Muriqui

• Referenced in 1 article [sw32925]
• Muriqui Optimizer is a solver of convex Mixed Integer Nonlinear Programming (MINLP) problems. Moreover, Muriqui ... applied to non-convex problems, without the guarantee of obtaining optimal solution. Muriqui implements...

• FLO

• Referenced in 2 articles [sw12272]
• multiobjective optimization (e.g. concept of Edgeworth-Pareto efficiency). Solving special classes of non-convex single...

• MIDACO

• Referenced in 3 articles [sw04775]
• several hundreds to some thousands of optimization variables. MIDACO implements a derivative-free, heuristic algorithm ... contain critical function properties such as non-convexity, discontinuities or stochastic noise. For cpu-time...

• MISQPOA

• Referenced in 1 article [sw07024]
• algorithm and to guarantee global optimlity for convex problems. A mixed-integer linear programming master ... determine a lower bound. Afterwards, a nonlinear optimization program is generated to improve the best ... non-convex and non-relaxable nonlinear mixed-integer programs, but without guaranteeing global optimality...

• LinAIG

• Referenced in 6 articles [sw10316]
• representation called LinAIGs. LinAIGs represent (possibly non-convex) polyhedra extended by Boolean variables. Key components ... Satisfiability Modulo Theories) solvers. Constraint minimization optimizes polyhedra by exploiting the fact that states already...

• picasso

• Referenced in 4 articles [sw20406]
• enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which ... convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation ... unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using...

• Opytimizer

• Referenced in 1 article [sw31846]
• control engineering, among others. Nevertheless, traditional iterative optimization methods use the evaluation of gradients ... computational burden and when working with non-convex functions. Recent biological-inspired methods, known ... though they do not guarantee to find optimal solutions, they usually find a suitable solution...

• 2-Phase NSGA II

• Referenced in 2 articles [sw28524]
• risk measurements algorithm in portfolio optimization. Portfolio optimization is a serious challenge for financial engineering ... world that ultimately lead to a non-convex search space such as cardinality constraint ... paper, a new efficient multi-objective portfolio optimization algorithm called 2-phase NSGA II algorithm...

• ConRad

• Referenced in 2 articles [sw30420]
• convex optimization approach to radiation treatment planning with dose constraints. We present a method ... handling dose constraints as part of a convex programming framework for inverse treatment planning ... part of a convex formulation. Since dose-volume constraints are non-convex, we replace them...