Topic: optimization-algorithm-library Goto Github
Some thing interesting about optimization-algorithm-library
Some thing interesting about optimization-algorithm-library
optimization-algorithm-library,pymhlib - A Toolbox for Metaheuristics and Hybrid Optimization Methods
Organization: ac-tuwien
optimization-algorithm-library,The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, and high similarity between their components' interactions. This study attempts to go beyond the traps of metaphors and introduce a novel metaphor-free population-based optimization based on the mathematical foundations and ideas of the Runge Kutta (RK) method widely well-known in mathematics. The proposed RUNge Kutta optimizer (RUN) was developed to deal with various types of optimization problems in the future. The RUN utilizes the logic of slope variations computed by the RK method as a promising and logical searching mechanism for global optimization. This search mechanism benefits from two active exploration and exploitation phases for exploring the promising regions in the feature space and constructive movement toward the global best solution. Furthermore, an enhanced solution quality (ESQ) mechanism is employed to avoid the local optimal solutions and increase convergence speed. The RUN algorithm's efficiency was evaluated by comparing with other metaheuristic algorithms in 50 mathematical test functions and four real-world engineering problems. The RUN provided very promising and competitive results, showing superior exploration and exploitation tendencies, fast convergence rate, and local optima avoidance. In optimizing the constrained engineering problems, the metaphor-free RUN demonstrated its suitable performance as well. The authors invite the community for extensive evaluations of this deep-rooted optimizer as a promising tool for real-world optimization. The source codes, supplementary materials, and guidance for the developed method will be publicly available at different hubs at http://aliasgharheidari.com/RUN.html.
User: aliasgharheidaricom
Home Page: https://aliasgharheidari.com/RUN.html
optimization-algorithm-library,Query Language module for PmDB
User: davisdevelopment
optimization-algorithm-library,Python library for solving large-scale inverse problems
User: fpicetti
optimization-algorithm-library,implementations of optimization algorithms for regularized empirical risk minimization
User: husk214
optimization-algorithm-library,Python package for executing optimization algorithm.
User: mdabrowski1990
optimization-algorithm-library, A genetic algorithm simulation game using OptivolutionPy & Processing3.
User: mhmd-hisham
optimization-algorithm-library,LibOptimization is numerical optimization algorithm library for .NET Framework. / .NET用の数値計算、最適化ライブラリ
User: tomitomi3
optimization-algorithm-library,A Python implementation of the paper "Duelist Algorithm: An Algorithm Inspired by How Duelist Improve Their Capabilities in a Duel" https://arxiv.org/abs/1512.00708
User: tsyet12
optimization-algorithm-library,C++ implementation of the Interior Point Methods (CPPIPM)
User: yimingyan
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