Libmoon is a flexible and extensible multi-objective optimization platform. Our goal is to make MOO great again. We released libmoon not because developing MOO is easy, but because it is hard.
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Updated
Jun 12, 2024 - Python
Libmoon is a flexible and extensible multi-objective optimization platform. Our goal is to make MOO great again. We released libmoon not because developing MOO is easy, but because it is hard.
Experimental design and (multi-objective) bayesian optimization.
Official implementation of TEVC'2024 paper "Hypervolume-Guided Decomposition for Parallel Expensive Multiobjective Optimization"
Source code for "Evolution of Adaptive Force Chains in Reconfigurable Granular Metamaterials"
Code for "Evolving Variable Stiffness Fiber Patterns for Multi-shape Robotic Sheets", Parsa et al., Robosoft 2023
Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization
Feature Selection Library for Data Sciences in Python
A framework for single/multi-objective optimization with metaheuristics
L2O/NCO codes from CIAM Group at SUSTech, Shenzhen, China
A PyTorch Library for Multi-Task Learning
JUlia augMENted ε-consTraint Optimisation (Jumento) - A package with AUGMECON and AUGMECON 2
EA codes from CIAM Group at SUSTech, Shenzhen, China
Code regarding a multiobjective optimization of water usage and revenue for agricultural commodities in Jordan from 2019
Multi- and many-objective optimization in generative chemistry model latent spaces.
Source code for the paper titled "Multi-Objective Optimization for Sparse Deep Multi-Task Learning"
Supplementary Material "Co-Design Optimisation of Morphing Topology and Control of Winged Drones" published in IEEE 2024 International Conference on Robotics and Automation (ICRA)
Multiobjective black-box optimization using gradient-boosted trees
Generalized Incremental Orthant Search: Towards efficient steady-state evolutionary multiobjective algorithms
Python library for parallel multiobjective simulation optimization
A personalized ride-sharing two-sided matching decision-making method considering passenger no-show behavior
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