AI constraint solver in Java to optimize the vehicle routing problem, employee rostering, task assignment, maintenance scheduling, conference scheduling and other planning problems.

A research toolkit for particle swarm optimization in Python

🍀 Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)

A Collection Of The State-of-the-art Metaheuristic Algorithms In Python (Metaheuristic/Optimizer/Nature-inspired/Biology)

Jenetics - Genetic Algorithm, Genetic Programming, Grammatical Evolution, Evolutionary Algorithm, and Multi-objective Optimization

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

🎯 A comprehensive gradient-free optimization framework written in Python

A framework for single/multi-objective optimization with metaheuristics

jMetal: a framework for multi-objective optimization with metaheuristics

EvoloPy toolbox provides classical and recent nature-inspired metaheuristic for the global optimization.

OptaPy is an AI constraint solver for Python to optimize planning and scheduling problems.

PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (evolutionary algorithms/swarm-based optimizers/pattern search/...). [https://pypop.rtfd.io/]

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

This toolbox offers more than 40 wrapper feature selection methods include PSO, GA, DE, ACO, GSA, and etc. They are simple and easy to implement.

Derivative-Free Global Optimization Algorithm (C++, Python binding) - Continuous, Discrete, TSP, NLS, MINLP

A MSc's Dissertation Project which focuses on Vehicle Routing Problem with Time Windows (VRPTW), using both exact method and heuristic approach (General Variable Neighbourhood Search)

Toolbox for gradient-based and derivative-free non-convex constrained optimization with continuous and/or discrete variables.

Artificial Bee Colony Algorithm in Python.

An evolutionary computation framework to (automatically) build fast parallel stochastic optimization solvers

OptFrame - C++17 (and C++20) 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, etc.