A PyTorch Library for Multi-Task Learning

Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization

A framework for single/multi-objective optimization with metaheuristics

jMetal: a framework for multi-objective optimization with metaheuristics

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

Experimental design and (multi-objective) bayesian optimization.

Learning how to implement GA and NSGA-II for job shop scheduling problem in python

Evolutionary & genetic algorithms for Julia

syftr is an agent optimizer that helps you find the best agentic workflows for your budget.

Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).

EvoMO is a GPU-accelerated library for evolutionary multiobjective optimization (EMO)

Official PyTorch Implementation for Conflict-Averse Gradient Descent (CAGrad)

An implementation of NSGA-III in Python.

[ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning

LibMOON is a standard and flexible framework to study gradient-based multiobjective optimization.

A very fast, 90% vectorized, NSGA-II algorithm in matlab.

Spatial Containers, Pareto Fronts, and Pareto Archives

L2O/NCO codes from CIAM Group at SUSTech, Shenzhen, China

Python library for parallel multiobjective simulation optimization

一个疫情背景下应急物资配送算法：用改进后的多目标粒子群优化（MOPSO）算法解决带有风险矩阵的多辆车配送旅行商问题（TSP）