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57 314 (0,203s)

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The Constrained Optimization Problem and the Risk of Using the Method of Lagrange Multipliers

Main topics of the document: Lagrange multipliers; extreme-value theorem; constrained optimization problem...

BA - Obecná matematika

  • 2013
  • Jx
Result

L-SHADE with Competing Strategies Applied to Constrained Optimization

developed for bound-constrained optimization. In this paper, the LSHADE44 algorithm was slightly simplified and modified to be able to solve constrained problems. The benchmark set arranged forCEC2017 competition on co...

Applied mathematics

  • 2017
  • D
Result

Automatically Generated Genetic Algorithms for Constrained Mixed Programming in Materials Science

The paper addresses key problems pertaining to the commonly used evolutionary approach to optimization in materials science. It proposes an approach to mixed constrained problems formulating a separate optimization task for...

IN - Informatika

  • 2007
  • D
Result

Numerical (Constrained) Optimization in Wolfram Mathematica

Software for numerical (constrained) optimization using few algorithms, such as Differential Evolution, Simulated Annealing, Nelder-Mead, Random Search and with the possibility of setting many parameters....

IN - Informatika

  • 2013
  • R
  • Link
Result

On vector optimality conditions for constrained problems with l-stable data

The aim of this paper is to enhance certain optimality conditions for constrained vector programming problem with l-stable data published by [GINCHEV, I.: On scalar and vector l-stable functions, Nonlinear Anal. 74 (2011), 182-194],...

BA - Obecná matematika

  • 2016
  • Jx
  • Link
Result

Convergence Rate for Diminishing Stepsize Methods in nonconvex Constrained Optimization via Ghost Penalties

for a diminishing stepsize method for nonconvex, constrained optimization problems.This is a companion paper to “Ghost penalties in nonconvex constrained optimization: Diminishing stepsizes and iteration complexit...

Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

  • 2020
  • JSC
  • Link
Result

A Note on Optimization under Uncertainty: Comparing Probabilistically Constrained and Robust Optimization Methodology

. In this paper, we concentrate on two specific approaches, namely on chance constrained (stochastic) and robust optimization. Chance (probabilistically) constrained optimizationDealing with optimization p...

BB - Aplikovaná statistika, operační výzkum

  • 2016
  • D
Result

A new polynomially solvable class of quadratic optimization problems with box constraints

Main topics of the document: quadratic optimization; box-constrained optimization; low-rank matrix; zonotope; computational complexity......

Statistics and probability

  • 2021
  • Jimp
  • Link
Result

Sample variance over interval data: comparison of optimization algorithms in MATLAB

Basic themes of document: sample variance; interval data; constrained nonlinear optimization algorithms...

Statistics and probability

  • 2017
  • D
  • Link
Result

Robust portfolio optimization: a Stochastic Evaluation of Worst-Case Scenarios

Main topics of the document: optimization; portfolio; risk; robust optimization; stochastic evaluation; chance constrained DEA; worst-case markets......

Finance

  • 2023
  • JSC
  • Link
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