metaheuristics

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

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

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

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

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

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

🎯 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.

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

Solving VRPTW with metaheuristics

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