Optimisation Python Packages

optimistix

Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/

linopy

Linear optimization with N-D labeled arrays in Python

pypsa

PyPSA: Python for Power System Analysis

bluepyopt

Blue Brain Python Optimisation Library

bluepyemodel

Blue Brain Python Electrical Modeling Pipeline

pyvmcon

Python implementation of the VMCON non-linear constrained optimiser.

finquant

A program for financial portfolio management, analysis and optimisation

flatland-rl

The Flatland Framework is a multi-purpose environment to tackle problems around resilient resource allocation under uncertainty. It is designed to be a flexible and method agnostic to solve a wide range of problems in the field of operations research and reinforcement learning.

flixopt

Progressive flow system optimization in Python - start simple, scale to complex.

cobyqa

A derivative-free solver for general nonlinear optimization.

calliope

A multi-scale energy systems modelling framework.

dlux

Differentiable Physical Optics Propagation in Jax

calisim

A toolbox for the calibration and evaluation of simulation models.

myspokenlanguagedetection

Spoken language identification with CNN and RNN - Improved Version: accuracy up

district-energy-model

District Energy Model

macop

Minimalist And Customisable Optimisation python Package

pykp

Tooling for sampling and solving instances of the 0-1 Knapsack Problem

compas-shapeop

ShapeOp wrapper for COMPAS.

insurance-optimise

Constrained portfolio rate optimisation for insurance pricing — SLSQP, FCA ENBP, efficient frontier, shadow prices, JSON audit trail

xad

High-Performance Automatic Differentiation for Python

tide-feature-selection

Feature selection for real ML pipelines: filters, wrappers, and metaheuristics with cross-validation, reproducibility, and bundled benchmarks.

edo

A library for generating artificial datasets through genetic evolution.

samo

Streaming Architecture Mapping Optimiser

mooda-dna

A DNA design and assembly method based on multi-objective optimization.