A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
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Updated
Jul 4, 2024 - C++
A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
An evolutionary computation framework to (automatically) build fast parallel stochastic optimization solvers
ALNS header-only library (loosely) based on the original implementation by Stefan Ropke.
A Fast Iterated-Local-Search Localized Optimization algorithm for the CVRP.
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.
Derivative-Free Global Optimization Method (C++, Python binding)
A set of reusable components for fast prototyping CVRP heuristic solution approaches.
This code is to solve traveling salesman problem by using simulated annealing meta heuristic.
A C++ framework to couple optimisation tools and simulation models
A decision support system for the two-dimensional strip packing problem
C++ metaheuristics modeler/solver for general integer optimization problems.
Grey Wolf Optimizer (+ PSO for comparison) algorithm implementation in C++ with Python bindings
Job Shop Scheduling metaheuristics
Using GRASP and ILS to solve a multi-objective (TSP + Knapsack) problem
mFET is free timetabling software (licensed under the GNU Affero General Public License version 3 or later). This program aims to automatically generate the timetable of a school, high-school or university. It may be used for other timetabling purposes.
Práctica 1 de la asignatura Metaheurísticas de la Universidad de Granada (UGR)
Timetabling solver for higher education institutions
Bandwidth Multi Coloring Problem slover written in C++. The metaheuristic is based on genetic and greedy algorithms.
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