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
Library for Jacobian descent with PyTorch. It enables the optimization of neural networks with multiple losses (e.g. multi-task learning).
Evolutionary & genetic algorithms for Julia
syftr is an agent optimizer that helps you find the best agentic workflows for your budget.
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）
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