Search Packages

fcmaes

A Python 3 gradient-free optimization library

mo-gymnasium

Multi-objective Gymnasium environments for reinforcement learning

landscapes

A dependency free library of standardized optimization test functions written in pure Python.

moead-framework

MOEA/D is a general-purpose algorithm framework. It decomposes a multi-objective optimization problem into a number of single-objective optimization sub-problems and then uses a search heuristic to optimize these sub-problems simultaneously and cooperatively.

morl-baselines

Multi-Objective Reinforcement Learning algorithms implementations.

ezr

Explainable multi-objective optimization

harmonix-opt

Harmony Search optimization library with dependent variable spaces, engineering catalogs (ACI rebar, steel sections, concrete grades), dynamic bandwidth, crash recovery, and CSV logging.

pyhsds

Harmony Search optimization library with dependent variable spaces, engineering catalogs (ACI rebar, steel sections, concrete grades), dynamic bandwidth, crash recovery, and CSV logging.

mobo

A rational and extensible algorithm for solving multi-objective optimization problems

deepcoord

DeepCoord: Self-Learning Network and Service Coordination Using Deep Reinforcement Learning