jMetal: a framework for multi-objective optimization with metaheuristics
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Updated
Mar 24, 2026 - Java
jMetal: a framework for multi-objective optimization with metaheuristics
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
Learning how to implement GA and NSGA-II for job shop scheduling problem in python
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
Evolutionary & genetic algorithms for Julia
An implementation of NSGA-III in Python.
Experimental design and (multi-objective) bayesian optimization.
An open source fullstack framework for interactive multiobjective optimization and decision-support..
A Python implementation of the decomposition based multi-objective evolutionary algorithm (MOEA/D)
A very fast, 90% vectorized, NSGA-II algorithm in matlab.
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)
[ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning
🔧 🐝 A set of classes implementing single- and multi-objective Particle Swarm Optimization techniques for Cloudlet scheduling and WSN Localization optimizations. This code is part of the thesis titled "Optimizing Cloudlet Scheduling and Wireless Sensor Localization using Computational Intelligence Techniques", by Hussein S. Al-Olimat at UT.
L2O/NCO codes from CIAM Group at SUSTech, Shenzhen, China
an implementation of NSGA-II in java
Genetic algorithms applied in Computer Fluid Dynamics for multiobjective optimization - Senior Thesis in Mechanical Engineering at the University of Vermont
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.
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