• LMI toolbox

  • Referenced in 1429 articles [sw06383]
  • significantly faster than classical convex optimization algorithms, it should be kept in mind that ... today’s workstations. However, research on LMI optimization is still very active and substantial speed...
  • KELLEY

  • Referenced in 610 articles [sw04829]
  • optimization This book gives an introduction to optimization methods for unconstrained and bound constrained minimization ... complete generality and confine our scope to algorithms that are easy to implement ... approximately 100 pages, is devoted to the optimization of smooth functions. The methods studied ... used to demonstrate the behavior of optimization algorithms. Chapter 7 introduces implicit filtering, a technique...
  • L-BFGS

  • Referenced in 735 articles [sw03229]
  • Algorithm 778: L-BFGS-B Fortran subroutines for large-scale bound-constrained optimization. L-BFGS ... limited-memory algorithm for solving large nonlinear optimization problems subject to simple bounds ... this case performs similarly to its predecessor, algorithm L-BFGS (Harwell routine VA15). The algorithm...
  • ABC

  • Referenced in 270 articles [sw10950]
  • powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. Swarm intelligence ... Colony (ABC) Algorithm is an optimization algorithm based on the intelligent behaviour of honey ... swarm. In this work, ABC algorithm is used for optimizing multivariable functions and the results...
  • minpack

  • Referenced in 696 articles [sw05310]
  • relevant to the development of software for optimization libraries. In the second part I illustrate ... first part by discussing algorithms for unconstrained optimization. Because the discussion in this part...
  • LANCELOT

  • Referenced in 299 articles [sw00500]
  • design and implementation of large-scale optimization algorithms...
  • EGO

  • Referenced in 349 articles [sw07588]
  • Efficient Global Optimization (EGO) algorithm solves costly box-bounded global optimization problems with additional linear...
  • SVMlight

  • Referenced in 261 articles [sw04076]
  • learning a ranking function. The optimization algorithms used in SVMlight are described in [Joachims, 2002a ... transductive SVMs. The algorithm proceeds by solving a sequence of optimization problems lower-bounding ... local search. A detailed description of the algorithm can be found in [Joachims, 1999c...
  • Genocop

  • Referenced in 1081 articles [sw04707]
  • genetic algorithm-based program for constrained and unconstrained optimization, written in C. The Genocop system...
  • CUTE

  • Referenced in 218 articles [sw14681]
  • testing small- and large-scale nonlinear optimization algorithms. Although many of these facilities were originally ... available to researchers for their development of optimization software. The tools can be obtained...
  • Optimization Toolbox

  • Referenced in 286 articles [sw10828]
  • perform tradeoff analyses, and incorporate optimization methods into algorithms and applications...
  • SNOPT

  • Referenced in 518 articles [sw02300]
  • SNOPT: An SQP algorithm for large-scale constrained optimization. Sequential quadratic programming (SQP) methods have ... proved highly effective for solving constrained optimization problems with smooth nonlinear functions in the objective ... gradients are sparse. We discuss an SQP algorithm that uses a smooth augmented Lagrangian merit ... Lagrangian and uses a reduced-Hessian algorithm (SQOPT) for solving the QP subproblems...
  • Scilab

  • Referenced in 167 articles [sw00834]
  • various types of plots and charts. Optimization: Algorithms to solve constrained and unconstrained continuous ... discrete optimization problems. Statistics: Tools to perform data analysis and modeling Control System Design & Analysis ... Standard algorithms and tools for control system study Signal Processing: Visualize, analyze and filter signals...
  • Adam

  • Referenced in 345 articles [sw22205]
  • Method for Stochastic Optimization. We introduce Adam, an algorithm for first-order gradient-based optimization ... require little tuning. Some connections to related algorithms, on which Adam was inspired, are discussed ... analyze the theoretical convergence properties of the algorithm and provide a regret bound ... best known results under the online convex optimization framework. Empirical results demonstrate that Adam works...
  • LBFGS-B

  • Referenced in 335 articles [sw05142]
  • Algorithm 778: L-BFGS-B Fortran subroutines for large-scale bound-constrained optimization L-BFGS ... limited-memory algorithm for solving large nonlinear optimization problems subject to simple bounds ... this case performs similarly to its predecessor, algorithm L-BFGS (Harwell routine VA15). The algorithm...
  • CEC 05

  • Referenced in 169 articles [sw18811]
  • conducted on some real-parameter optimization algorithms. The codes in Matlab, C and Java...
  • simannf90

  • Referenced in 118 articles [sw05059]
  • From authors’ summary: A new global optimization algorithm for functions of continuous variables is presented ... annealing” algorithm recently introduced in combinatorial optimization. The algorithm is essentially an iterative random search...
  • LAPACK

  • Referenced in 1642 articles [sw00503]
  • LAPACK addresses this problem by reorganizing the algorithms to use block matrix operations, such ... innermost loops. These block operations can be optimized for each architecture to account...
  • ISOLATE

  • Referenced in 213 articles [sw07741]
  • that framework, a new algorithm is presented, which is optimal in terms of memory usage ... input polynomial. From this new algorithm, we derive an adaptive semi-numerical version, using multi ... that these critical optimizations have important consequences since our new algorithm still works with huge...
  • NLopt

  • Referenced in 91 articles [sw11789]
  • free optimization routines available online as well as original implementations of various other algorithms ... parameter. Support for large-scale optimization (some algorithms scalable to millions of parameters and thousands ... constraints). Both global and local optimization algorithms. Algorithms using function values only (derivative-free ... algorithms exploiting user-supplied gradients. Algorithms for unconstrained optimization, bound-constrained optimization, and general nonlinear...