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@MISC{Muzakka:1053860,
author = {Muzakka, Khoirul Faiq and Möller, Sören and Finsterbusch,
Martin},
title = {{M}inion : a high-performance derivative-free optimization
library designed for solving complex optimization problems.},
reportid = {FZJ-2026-01558},
year = {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},
cin = {IMD-2},
cid = {I:(DE-Juel1)IMD-2-20101013},
pnm = {1222 - Components and Cells (POF4-122)},
pid = {G:(DE-HGF)POF4-1222},
typ = {PUB:(DE-HGF)33},
url = {https://juser.fz-juelich.de/record/1053860},
}