NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO

A PyTorch Library for Multi-Task Learning

Evolutionary multi-objective optimization platform

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

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

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

🛍 A real-world e-commerce dataset for session-based recommender systems research.

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

High-performance metaheuristics for optimization coded purely in Julia.

Jupyter/IPython notebooks about evolutionary computation.

Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology

Deep Reinforcement Learning for Multiobjective Optimization. Code for this paper

[ECCV2020] NSGANetV2: Evolutionary Multi-Objective Surrogate-Assisted Neural Architecture Search

Multi-Task Learning Framework on PyTorch. State-of-the-art methods are implemented to effectively train models on multiple tasks.

AutoOED: Automated Optimal Experimental Design Platform

Transforming Neural Architecture Search (NAS) into multi-objective optimization problems. A benchmark suite for testing evolutionary algorithms in deep learning.

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

A comprehensive list of gradient-based multi-objective optimization algorithms in deep learning.

Multi-objective Bayesian optimization

OptFrame - C++17/C++20/C++23 Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hyperheuristics: Genetic Algorithm, Simulated Annealing, Tabu Search, Iterated Local Search, Variable Neighborhood Search, NSGA-II, Genetic Programming etc. Examples for Traveling Salesman, Vehicle Routing, Knapsack Problem, etMu

Generalized and Efficient Blackbox Optimization System.

A Julia package for solving multi-objective optimization problems

Library for Multi-objective optimization in Gradient Boosted Trees

A Universal Deep Reinforcement Learning Framework

Compute the Pareto (non-dominated) set, i.e., skyline operator/query.

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

A curated list of awesome multi-objective optimization research resources.

[ICLR 2025] The offical implementation of "PSEC: Skill Expansion and Composition in Parameter Space", a new framework designed to facilitate efficient and flexible skill expansion and composition, iteratively evolve the agents' capabilities and efficiently address new challenges

MATLAB Tool for Multi-Objective Optimization

Yuck is a local-search constraint solver with FlatZinc interface