2025-07-24 –, Main Room 2
is a new Julia package designed to bring recent powerful metaheuristic optimization algorithms to the Julia ecosystem. It includes more than 100 different metaheuristic optimization algorithms. These algorithms have been carefully implemented and are ready to help solve your optimization problems. Implementing the CEC benchmark for performance evaluation, future plans include the full CEC suite and expanding to ~300 optimization algorithms.
MetaheuristicsAlgorithms.jl, a new Julia package designed to bring recent powerful metaheuristic optimization algorithms to the Julia ecosystem. These algorithms, originally developed in MATLAB or Python, have now been ported to Julia. By leveraging Julia’s strengths, this package offers significantly faster execution speeds compared to traditional languages, making it ideal for solving complex optimization problems in various fields such as engineering, artificial intelligence, and beyond. With a growing set of optimization algorithms and future enhancements, this package will help you tackle a wide range of optimization challenges efficiently.
MetaheuristicsAlgorithms.jl initially includes more than 100 different metaheuristic optimization algorithms. These algorithms have been carefully implemented and are ready to help solve your optimization problems. Looking ahead, the package will be expanded to include more algorithms and improvements, ensuring it stays up-to-date with the latest advancements in optimization methods. Additionally, we plan to integrate benchmark functions from renowned CEC (Congress on Evolutionary Computation) competitions, including those from CEC 2005, 2014, 2017, 2020, and 2022, giving users a broader toolkit for testing and comparing algorithms in standard scenarios.
MetaheuristicsAlgorithms.jl is just the beginning of a larger vision. In the future, we will continue to expand this package to include more metaheuristic algorithms, additional benchmark functions from the CEC competitions, and improved features to make it even more useful for optimization research and applications. The package is designed to be flexible, fast, and easy to use, allowing the Julia community to engage with cutting-edge optimization techniques and contribute to its growth.
