Reverse Dependencies of pymoo

The following projects have a declared dependency on pymoo:

• adaptdl-sched — Dynamic-resource trainer and scheduler for deep learning
• adaptdl-sched-modified-pandyaka — Dynamic-resource trainer and scheduler for deep learning
• altrios — Tool for modeling and optimization of advanced locomotive powertrains for freight rail decarbonization.
• artap — Platform for robust design optimization
• autocode-py — autocode: Auto Code Improvement by Metrics Optimization.
• automlmoo — A package for automatic modeling and optimize systems based on data
• blackboxopt — A common interface for blackbox optimization algorithms along with useful helpers like parallel optimization loops, analysis and visualization scripts.
• CADET-Process — A Framework for Modelling and Optimizing Advanced Chromatographic Processes
• CADETMatch — CADETMatch is a parameter estimation and error modeling library for CADET
• comets — CoMETS, the Cosmo Model Experimentation Toolbox, is a Python library for experimenting with numerical models and simulators
• constrained-attacks — constrained-attacks is a framework to generate adversarial examples under domain specific constraints.
• corrai — Data correction and Machine Learning
• cuBNM — A toolbox for biophysical network modeling on GPUs
• decode-mcd — MCD generates counterfactuals that meet multiple, customizable objectives in both the feature and performance spaces.
• deephyper — Scalable asynchronous neural architecture and hyperparameter search for deep neural networks
• dmpe — Excitation of exciting systems through differentiable predictive excitation
• dovado-rtl — RTL Design Space Exploration on top of Vivado
• dynast — DyNAS-T (Dynamic Neural Architecture Search Toolkit) - a SuperNet NAS optimization package
• ebcpy — Python Library used for different python modules for the analysis and optimization of energy systems, buildings and indoor climate
• edbojz — Bayesian reaction optimization as a tool for chemical synthesis.
• ex-fuzzy — Library to perform explainable AI using fuzzy logic.
• EZFF — Multiobjective forcefield optimization for Molecular Dynamics
• feloopy — FelooPy: Efficient and feature-rich integrated decision environment
• femder — A simple acoustic FEM package
• femupy — Finite element model updating using natural frequencies and mode shapes
• foxes-opt — Wind farm optimization for the FOXES package
• gemseo-pymoo — A GEMSEO wrapper for pymoo optimization algorithms.
• gendgn — Python-based command line tool for generative design using IFC file format
• georges — Georges' accelerator physics library - Core
• HEBO — Heteroscedastic evolutionary bayesian optimisation
• HEBO-mindspore — Heteroscedastic evolutionary bayesian optimisation
• hydrowizard — HydroWizard: State-of-the-art water basin modeling, optimization, and simulation using neural networks, genetic algorithms, and DAGs.
• hyper-ford — HYdroPowER Simulation and Optimization Toolbox
• ionbench — A benchmarking tool for comparing different parameter optimization algorithms for ion channel models
• iwopy — Fraunhofer IWES optimization tools in Python
• libmoon — Moon, Make MOO great again
• LightWin — Automatically compensate cavity failures in linacs
• metrics-as-scores — Interactive web application, tool- and analysis suite for approximating, exploring, understanding, and sampling from conditional distributions.
• MINSGA3 — A modification of Pymoo library's NSGA3 algorithm to work with Mixed-Integer problems
• mo-gym — Environments for Multi-Objective RL.
• morl-baselines — Implementations of multi-objective reinforcement learning (MORL) algorithms.
• nemo-bo — Multi-objective optimization of chemical processes with automated machine learning workflows
• nevergrad — A Python toolbox for performing gradient-free optimization
• nmoo — A wrapper-based framework for pymoo problem modification.
• nncf — Neural Networks Compression Framework
• opensbt — OpenSBT is a Modular Framework for Search-based Testing of Automated Driving Systems
• OptiMOBO — Solve multi-objective problems using Bayesian optimisation.
• osier — osier: A justice oriented energy system optimization tool
• paref — Pareto reflection based multi-objective optimization
• pdopt — Package for Probabilistic Design Space Exploration using Set-Based Design
• ProteoformQuant — A python command line tool for the quantification of peptidoform/proteoforms
• pyanno4rt — A package for Python-based advanced numerical nonlinear optimization in radiotherapy.
• pyaugmecon — An AUGMECON based multi-objective optimization solver for Pyomo.
• pybrops — Python package for breeding program numerical optimization and simulation
• pycellga — A Python Package for Improved Cellular Genetic Algorithms
• PyEGRO — A Python library for efficient global robust optimization
• pyfomo — Fairness oriented Multi-objective Optimization
• pyLIMA — Microlsening analysis package.
• pymob — Modelling platform for Python
• pymoode — A Python optimization package using Differential Evolution.
• pyuncertainnumber — Rigorous computation with Uncertain Number in Python
• quant1x — Quant1X量化交易框架
• ropt-pymoo — A pymoo plugin for the ropt robust optimization library
• rtb-toolbox — no summary
• sb-arch-opt — SBArchOpt: Surrogate-Based Architecture Optimization
• scmagneto — MAGNETO: Marker pAnels GeNEraTor with multi-Objective optimization
• sdc-scissor — A cost-effective test selection for self-driving cars in virtual environments
• sober — sober optimises built environment robustly
• summit — Tools for optimizing chemical processes
• syne-tune — Distributed Hyperparameter Optimization on SageMaker
• t3co — NREL's Transportation Technology Total Cost of Ownership tool
• tabularbench — TabularBench: Adversarial robustness benchmark for tabular data
• trieste — A Bayesian optimization research toolbox built on TensorFlow
• tuneup — Global optimizer comparison and combination
• vertibench — A tool for benchmarking vertical federated learning algorithms, containing synthetic data split and data evaluation.
• wmsd — TOPSIS ranking and interpretation using WMSD-space
• xmoai — eXplainable Artificial Intelligence using Multiobjective Optimization
• zfista — A globally convergent fast iterative shrinkage-thresholding algorithm with a new momentum factor for single and multi-objective convex optimization