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.

Evolutionary & genetic algorithms for Julia

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

Experimental design and (multi-objective) bayesian optimization.

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

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

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

An implementation of NSGA-III in Python.

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

Spatial Containers, Pareto Fronts, and Pareto Archives

A Python implementation of the decomposition based multi-objective evolutionary algorithm (MOEA/D)

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）

Capacitated vehicle routing problem implemented in python using DEAP package. Non dominated sorting Genetic algorithm is used to solve Multiobjective problem of minimizing Total distance travelled by all vehicles and minimizing total number of vehicles at same time.

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

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