• ECOS

  • Referenced in 35 articles [sw12123]
  • open-source numerical software package for solving optimization problems with second-order cone constraints (SOCPs ... includes linear (LPs), quadratic (QPs), and quadratically-constrained quadratic programs (QCQPs). ECOS also supports ... variables by employing a simple branch and bound technique. ECOS is written entirely in ANSI ... consequence, it can be used to solve optimization problems on any embedded system for which...
  • OSGA

  • Referenced in 5 articles [sw16542]
  • User’s Manual for OSGA (Optimal SubGradient Algorithm). This document provides a user’s guide ... solving large-scale unconstrained, bound-constrained, and simply constrained convex optimization...
  • TRICE

  • Referenced in 46 articles [sw05197]
  • keep strict feasibility with respect to the bound constraints by using an affine scaling method ... Coleman} and {it Y. Li} [SIAM J. Optim ... they exploit trust-region techniques for equality-constrained optimization. Thus, they allow the computation...
  • SLMQN

  • Referenced in 2 articles [sw00879]
  • Newton method for large-scale bound constrained nonlinear optimization. SLMQN is a subspace limited memory ... quasi-Newton algorithm for solving large-scale bound constrained nonlinear programming problems. The algorithm...
  • libbrkga

  • Referenced in 1 article [sw13245]
  • Python/C++ library for bound-constrained global optimization using a biased random-key genetic algorithm. This ... genetic algorithm (BRKGA) for bound constrained global optimization. BRKGA (J Heuristics 17:487-525, 2011b...
  • MLOCPSOA

  • Referenced in 1 article [sw05055]
  • MLOCPSOA is a solver for bound constrained optimization, base on the particle swarm paradigm. MLOCPSOA...
  • SQOPT

  • Referenced in 17 articles [sw07860]
  • practical anti-degeneracy procedure, scaling, and elastic bounds on any number of constraints and variables ... SNOPT package for large-scale nonlinearly constrained optimization. The source code is re-entrant...
  • Intsolver

  • Referenced in 3 articles [sw08787]
  • used to bound ALL solutions of nonlinear optimization problem, equality constrained or not as well ... through the analysis of some important global optimization examples that we provide with the main...
  • ARGONAUT

  • Referenced in 5 articles [sw20651]
  • global optimization of general constrained grey-box problems. ARGONAUT incorporates variable selection, bounds tightening ... representations of unknown equations, which are globally optimized. ARGONAUT is tested on a large...
  • GLOPT

  • Referenced in 19 articles [sw00359]
  • global minimizer. \parGLOPT uses a branch and bound technique to split the problem recursively into ... block separable structure of the optimization problem. \parIn this paper we discuss a new reduction ... ways for generating feasible points of constrained nonlinear programs. These are implemented as the first...
  • TRESNEI

  • Referenced in 14 articles [sw05208]
  • trust-region Gauss-Newton method for bound-constrained nonlinear least-squares problems is presented ... numerical comparison with functions from the Matlab Optimization Toolbox is carried...
  • Py-BOBYQA

  • Referenced in 1 article [sw32721]
  • BOBYQA: Derivative-Free Optimizer for Bound-Constrained Minimization. Py-BOBYQA is a flexible package...
  • SparseFIS

  • Referenced in 10 articles [sw13736]
  • kind of upper bound on a reasonable granularity. The second phase optimizes the rule weights ... squares error measure by applying a sparsity-constrained steepest descent-optimization procedure. Depending...
  • ibexMop

  • Referenced in 1 article [sw34657]
  • only a few approaches dealing with nonlinear optimization problems, when they consider multiple objectives ... interval branch & bound algorithm for solving nonlinear constrained biobjective optimization problems. Although the general strategy...
  • SnadiOpt

  • Referenced in 4 articles [sw14988]
  • general-purpose system for solving optimization problems with many variables and constraints. It minimizes ... linear or nonlinear function subject to bounds on the variables and sparse linear or nonlinear ... quadratic programming and for linearly constrained optimization, as well as for general nonlinear programs...
  • PESC

  • Referenced in 6 articles [sw17860]
  • general framework for constrained Bayesian optimization using information-based search. We present an information-theoretic ... framework for solving global black-box optimization problems that also have black-box constraints ... target objective. We take a bounded rationality approach and develop a partial update for PESC ... direction towards a unified solution for constrained Bayesian optimization...
  • SOFAR

  • Referenced in 3 articles [sw31665]
  • sparse singular value decomposition with orthogonality constrained optimization to learn the underlying association networks, with ... convexity-assisted nonconvex optimization, we derive nonasymptotic error bounds for the suggested procedure characterizing...
  • cumulativemm

  • Referenced in 3 articles [sw15628]
  • constrained project scheduling problem, state-of-the-art exact algorithms combine a Branch and Bound ... constraint handlers cumulativemm and gprecedencemm for the optimization framework SCIP. With the latter...
  • gprecedencemm

  • Referenced in 3 articles [sw15629]
  • constrained project scheduling problem, state-of-the-art exact algorithms combine a Branch and Bound ... constraint handlers cumulativemm and gprecedencemm for the optimization framework SCIP. With the latter...
  • cGOP

  • Referenced in 1 article [sw20093]
  • rigorously solving nonconvex optimization problems to global optimality. The package implements the GOP algorithm (Floudas ... Visweswaran, 1993), which is applicable to general constrained biconvex problems, using ... these problems using decomposition and branch-and-bound techniques. It also incorporates several improvements made ... Floudas, 1995). The algorithms use local optimization solvers (currently MINOS (Murtagh and Saunders...