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| Hauptseite > Publikationsdatenbank > Minion : a high-performance derivative-free optimization library designed for solving complex optimization problems. |
| Hauptseite > Publikationsdatenbank > Minion : a high-performance derivative-free optimization library designed for solving complex optimization problems. |
| Software | FZJ-2026-01558 |
; ;
2025
Abstract: Minion is a high-performance derivative-free optimization library designed for solving complex optimization problems where gradients are unavailable or unreliable. It implements state-of-the-art evolutionary algorithms, including top-performing methods from IEEE CEC competitions, which are often missing in standard optimization libraries such as SciPy, NLopt, OptimLib, pyGMO, and pagmo2.Minion is not only a solver but also a research platform for developing and testing new optimization algorithms. It includes benchmark functions from CEC competitions (2011, 2014, 2017, 2019, 2020, and 2022), providing a robust framework for algorithm evaluation and comparison.Features: State-of-the-art optimization algorithms: Implements JADE, L-SHADE, jSO, j2020, NL-SHADE-RSP, LSRTDE, and ARRDE (our novel Adaptive Restart-Refine DE algorithm). Parallelization-ready: Supports vectorized function evaluations, allowing seamless integration with multithreading and multiprocessing for high-performance optimization. Optimized C++ backend with a Python wrapper: Provides high efficiency with an easy-to-use Python API. CEC Benchmark Suite: Includes benchmark problems from 2011, 2014, 2017, 2019, 2020, and 2022 for rigorous testing and comparison
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