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GloMPO GloMPO GloMPO
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  • AMS Driver
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    • Molecular Dynamics
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  • Engines
    • ADF Molecular DFT
    • BAND Periodic DFT
    • DFTB Semi-empirical
    • ForceField AMBER, UFF, APPLE&P...
    • GFNFF Force field
    • Hybrid QM/MM and mixed methods
    • ML Potential Machine Learning potentials
    • MOPAC Semi-empirical
    • Quantum ESPRESSO Periodic DFT
    • VASP Periodic DFT
    • ReaxFF Reactive force field
    • ASE engine Use any ASE calculator
  • Meso/Macro
    • COSMO-RS Thermodynamic properties of fluids
    • Bumblebee OLED device modeling
    • Microkinetics
    • Zacros Kinetic Monte Carlo
  • Tools
    • GUI Graphical User Interface
    • ParAMS Parametrization tool
    • Simple Active Learning On-the-fly training of ML
    • OLED Deposition and Properties Multiscale OLED modeling
    • Reactions Discovery Automatic reaction-discovery workflow
    • ACE Reaction Network Generation of reaction networks
    • Conformers Conformers generation
    • MD Trajectory Analysis Analysis of MD trajectories
    • ChemTraYzer2 Detect reactions from MD simulations
    • Utilities Various utility tools
  • Scripting
    • Python Scripting Examples Examples for Python scripting
    • PLAMS Python Library for Automating Molecular Simulations
    • amspython Python stack shipped with AMS
    • pyCRS Python Scripting with COSMO-RS
    • SCM Base Library Python library with core modules
    • reactmap Atom mapping between reactants and products
    • Command-line tools
    • ASE calculator
    • pyZacros Python Library Zacros (Kinetic Monte Carlo)
  • AMS2026.1
  • Other versions
  • GloMPO
  • Introduction
  • General Optimization Tasks
  • Parallelism
  • Components
    • Manager
    • Optimizers
      • Optimizer Return Type
      • Abstract Base Optimizer
      • Adaptive Rate Monte Carlo Optimizer
      • CMA-ES
      • Nevergrad
      • SciPy Optimize
      • Grid-wise Evaluation ‘Optimizer’
      • Random ‘Optimizer’
    • Selectors
    • Generators
    • Exit Conditions
    • Stoppers
    • Checkpointing
    • Sensitivity Analysis
    • Extras
      • Named Tuples
      • Helpers
      • Wrappers
  • Logging Messages
  • User Interventions
  • Outputs
  • Required Citations
  1. Documentation /
  2. GloMPO /
  3. Components /
  4. Optimizers

Optimizers¶

Optimizers perform the actual task minimization. Several optimizers are started in parallel by GloMPO. The optimizer classes here are either implementations or wrappers around optimization algorithms.

Table of Contents

  • Optimizer Return Type
  • Abstract Base Optimizer
  • Adaptive Rate Monte Carlo Optimizer
  • CMA-ES
  • Nevergrad
  • SciPy Optimize
  • Grid-wise Evaluation ‘Optimizer’
  • Random ‘Optimizer’
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Optimizer Return Type

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