A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

A curated list of mathematical optimization courses, lectures, books, notes, libraries, frameworks and software.

A JuMP extension for Stochastic Dual Dynamic Programming

An intuitive modeling interface for infinite-dimensional optimization problems.

Artificial Bee Colony Algorithm in Python.

Templated C++/CUDA implementation of Model Predictive Path Integral Control (MPPI)

Python library for stochastic numerical optimization

An open-source parallel optimization solver for structured mixed-integer programming

Riemannian stochastic optimization algorithms: Version 1.0.3

[NeurIPS 2023] The PyTorch Implementation of Scheduled (Stable) Weight Decay.

Create Your Own Metropolis-Hastings Markov Chain Monte Carlo Algorithm for Bayesian Inference (With Python)

A simple implementation of SPSA with automatic learning rate tuning

A collection of papers and readings for non-convex optimization

Data-driven decision making under uncertainty using matrices

A julia implementation of the CMA Evolution Strategy for derivative-free optimization of potentially non-linear, non-convex or noisy functions over continuous domains.

Hessian-based stochastic optimization in TensorFlow and keras

[ICML 2021] The official PyTorch Implementations of Positive-Negative Momentum Optimizers.

Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)

An interactive visual simulator for distance-based protein folding

This repo demonstrates how to build a surrogate (proxy) model by multivariate regressing building energy consumption data (univariate and multivariate) and use (1) Bayesian framework, (2) Pyomo package, (3) Genetic algorithm with local search, and (4) Pymoo package to find optimum design parameters and minimum energy consumption.