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The CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, where the step size is adapted measuring the length of a so-called cumulative path. The cumulative path is a combination of the previous steps realized by the…

Machine Learning · Computer Science 2012-07-02 Alexandre Adrien Chotard , Anne Auger , Nikolaus Hansen

In the post-Moore era, main performance gains of black-box optimizers are increasingly depending on parallelism, especially for large-scale optimization (LSO). Here we propose to parallelize the well-established covariance matrix adaptation…

Neural and Evolutionary Computing · Computer Science 2024-10-14 Qiqi Duan , Chang Shao , Guochen Zhou , Minghan Zhang , Qi Zhao , Yuhui Shi

The CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, where the step size is adapted measuring the length of a so-called cumulative path. The cumulative path is a combination of the previous steps realized by the…

Machine Learning · Computer Science 2013-02-19 Alexandre Chotard , Anne Auger , Nikolaus Hansen

Carbon isotope labeling method is a standard metabolic engineering tool for flux quantification in living cells. To cope with the high dimensionality of isotope labeling systems, diverse algorithms have been developed to reduce the number…

Molecular Networks · Quantitative Biology 2022-02-11 Quentin Thommen , Julien Hurbain , Benjamin Pfeuty

To most existing non-equilibrium theories, the modeling of non-isothermal processes was a hard task. Intrinsic difficulties involved the non-equilibrium temperature, the coexistence of conserved energy and dissipative entropy, etc. In this…

Soft Condensed Matter · Physics 2019-02-26 Liangrong Peng , Yucheng Hu , Liu Hong

When faced with a specific optimization problem, choosing which algorithm to use is always a tough task. Not only is there a vast variety of algorithms to select from, but these algorithms often are controlled by many hyperparameters, which…

Neural and Evolutionary Computing · Computer Science 2020-01-07 Diederick Vermetten , Hao Wang , Carola Doerr , Thomas Bäck

Restart strategy helps the covariance matrix adaptation evolution strategy (CMA-ES) to increase the probability of finding the global optimum in optimization, while a single run CMA-ES is easy to be trapped in local optima. In this paper,…

Neural and Evolutionary Computing · Computer Science 2020-04-28 Yang Lou , Shiu Yin Yuen , Guanrong Chen , Xin Zhang

While evolutionary computation is well suited for automatic discovery in engineering, it can also be used to gain insight into how humans and organizations could perform more effectively. Using a real-world problem of innovation search in…

Neural and Evolutionary Computing · Computer Science 2023-07-04 Erkin Bahceci , Riitta Katila , Risto Miikkulainen

System identification is an exceptionally expansive topic and of remarkable significance in the discipline of signal processing and communication. Our goal in this paper is to show how simple adaptive FIR and IIR filters can be used in…

Signal Processing · Electrical Eng. & Systems 2018-07-19 Ibraheem Kasim Ibraheem

Black-box optimization is a very active area of research, with many new algorithms being developed every year. This variety is needed, on the one hand, since different algorithms are most suitable for different types of optimization…

Neural and Evolutionary Computing · Computer Science 2021-02-11 Anja Jankovic , Tome Eftimov , Carola Doerr

The problem of system identification for the Kalman filter, relying on the expectation-maximization (EM) procedure to learn the underlying parameters of a dynamical system, has largely been studied assuming that observations are sampled at…

Machine Learning · Computer Science 2024-06-28 Peter Halmos , Jonathan Pillow , David A. Knowles

In the field of evolutionary computation, one of the most challenging topics is algorithm selection. Knowing which heuristics to use for which optimization problem is key to obtaining high-quality solutions. We aim to extend this research…

Neural and Evolutionary Computing · Computer Science 2019-04-17 Diederick Vermetten , Sander van Rijn , Thomas Bäck , Carola Doerr

Evolution strategies (ESs) are zeroth-order stochastic black-box optimization heuristics invariant to monotonic transformations of the objective function. They evolve a multivariate normal distribution, from which candidate solutions are…

Numerical Analysis · Mathematics 2022-02-09 Youhei Akimoto , Anne Auger , Tobias Glasmachers , Daiki Morinaga

The ensemble smoother with multiple data assimilation (ES-MDA) is becoming a popular assisted history matching method. In its standard form, the method requires the specification of the number of iterations in advance. If the selected…

Numerical Analysis · Mathematics 2024-06-11 Alexandre A. Emerick

A new model for evolving Evolutionary Algorithms (EAs) is proposed in this paper. The model is based on the Multi Expression Programming (MEP) technique. Each MEP chromosome encodes an evolutionary pattern that is repeatedly used for…

Neural and Evolutionary Computing · Computer Science 2021-10-13 Mihai Oltean

In this paper, we propose an implicit staggered algorithm for crystal plasticity finite element method (CPFEM) which makes use of dynamic relaxation at the constitutive integration level. An uncoupled version of the constitutive system…

Numerical Analysis · Mathematics 2024-06-27 Pedro Areias , Charles dos Santos , Rui Melicio , Nuno Silvestre

We propose an energy-stable parametric finite element method (ES-PFEM) for simulating solid-state dewetting of thin films in two dimensions via a sharp-interface model, which is governed by surface diffusion and contact line (point)…

Numerical Analysis · Mathematics 2020-06-08 Quan Zhao , Wei Jiang , Weizhu Bao

In several real-world applications in medical and control engineering, there are unsafe solutions whose evaluations involve inherent risk. This optimization setting is known as safe optimization and formulated as a specialized type of…

Neural and Evolutionary Computing · Computer Science 2024-05-20 Kento Uchida , Ryoki Hamano , Masahiro Nomura , Shota Saito , Shinichi Shirakawa

The mutation process in evolution strategies has been interlinked with the normal distribution since its inception. Many lines of reasoning have been given for this strong dependency, ranging from maximum entropy arguments to the need for…

Neural and Evolutionary Computing · Computer Science 2025-04-11 Jacob de Nobel , Diederick Vermetten , Hao Wang , Anna V. Kononova , Günter Rudolph , Thomas Bäck

After a pedagogical introduction to the main concepts of synthetic photometry, colours and bolometric corrections in the Johnson-Cousins, 2MASS, and HST-ACS/WFC3 photometric systems are generated from MARCS synthetic fluxes for various…

Solar and Stellar Astrophysics · Physics 2014-09-15 Luca Casagrande , Don A. VandenBerg