There are 1 repository under multi-objective topic.
Multi-objective Gymnasium environments for reinforcement learning
Multi-Objective Reinforcement Learning algorithms implementations.
AutoOED: Automated Optimal Experimental Design Platform
A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS)
A Python 3 gradient-free optimization library
[NeurIPS 2020] Diversity-Guided Efficient Multi-Objective Optimization With Batch Evaluations
[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
A dependency free library of standardized optimization test functions written in pure Python.
Genetic Algorithm (GA) for a Multi-objective Optimization Problem (MOP)
DeepCoord: Self-Learning Network and Service Coordination Using Deep Reinforcement Learning
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.
Surrogate-Based Architecture Optimization toolbox
Python Multi-Objective Simulation Optimization: a package for using, implementing, and testing simulation optimization algorithms.
Bayesian Optimization and Uncertainty Analyses Tools
Paxplot is a Python visualization library for parallel coordinate plots based on matplotlib.
Code for the paper Optimistic Linear Support and Successor Features as a Basis for Optimal Policy Transfer - ICML 2022
An algorithm to calculate all pure strategy Nash equilibria in multi-objective games with quasiconvex utility functions
Multi-Objective Design using Sequential Quadratic programming
Multi-objective Bayesian optimisation framework.
The W-Model, a tunable Black-Box Discrete Optimization Benchmarking (BB-DOB) problem, implemented for the BB-DOB@GECCO Workshop.
Code for Paper "Gridless Evolutionary Approach for Line Spectral Estimation With Unknown Model Order"
Discrete-world as the name says
Code for "A Multi-Objective Test Selection Tool using Test Suite Diagnosability"
(Completed) Machine Learning and Multi-Objective Evolutionary Algorithms to Solve Real World Engineering Problems (MultiObjectiveOptimisation and ML)
The cMIBACO implementation for lightly robust solutions in MOGenConVRP under uncertainty.
Official implementation of PPSN'24 paper "Biased Pareto Optimization for Subset Selection with Dynamic Cost Constraints"
Queen's University - Data Mining (CISC 873)
Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models