Results 51 to 60 of about 3,655 (256)

Multi-objective topology design optimization combined with robust optimization

Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2023
Topology optimization (TO), which is a design optimization technique that does not require design parameters, has been attracting attention. TO has a high degree of freedom and can obtain a novel design shape suitable for desired purposes.
Akito MARUO, Norihiko ITANI, Ayano HASOME, Takashi YAMAZAKI, Hajime IGARASHI   +4 more
doaj   +1 more source

Well placement optimization with the covariance matrix adaptation evolution strategy and meta-models [PDF]

Computational Geosciences, 2011
The amount of hydrocarbon recovered can be considerably increased by finding optimal placement of non-conventional wells. For that purpose, the use of optimization algorithms, where the objective function is evaluated using a reservoir simulator, is needed. Furthermore, for complex reservoir geologies with high heterogeneities, the optimization problem
Bouzarkouna, Zyed, Ding, Didier Yu, Auger, Anne   +2 more
openaire   +2 more sources

Consensus Formation and Change are Enhanced by Neutrality

Advanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag, Janina A. Hoffmann, Tim Rogers, Christian A. Yates   +3 more
wiley   +1 more source

A Distributed Cooperative Co-evolutionary CMA Evolution Strategy for Global Optimization of Large-Scale Overlapping Problems

IEEE Access, 2019
Distributed cooperative co-evolution (DCC) is an effective way to solve large-scale optimization problems. The cooperative co-evolution methodology can reduce the optimizing complexity by dividing a large-scale problem into small subcomponents, and ...
Ya-Hui Jia, Yu-Ren Zhou, Ying Lin, Wei-Jie Yu, Ying Gao, Lu Lu   +5 more
doaj   +1 more source

Covariance Matrix Adaptation Evolution Strategy for Low Effective Dimensionality

CoRR
Despite the state-of-the-art performance of the covariance matrix adaptation evolution strategy (CMA-ES), high-dimensional black-box optimization problems are challenging tasks. Such problems often involve a property called low effective dimensionality (LED), in which the objective function is formulated with redundant dimensions relative to the ...
Kento Uchida, Teppei Yamaguchi, Shinichi Shirakawa   +2 more
openaire   +2 more sources

A covariance matrix adaptation evolution strategy in reproducing kernel Hilbert space

Genetic Programming and Evolvable Machines, 2019
The covariance matrix adaptation evolution strategy (CMA-ES) is an efficient derivative-free optimization algorithm. It optimizes a black-box objective function over a well-defined parameter space in which feature functions are often defined manually. Therefore, the performance of those techniques strongly depends on the quality of the chosen features ...
Viet-Hung Dang, Ngo Anh Vien, T. J. Chung   +2 more
openaire   +2 more sources

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 more
wiley   +1 more source

A Data‐Driven Inverse Design Methodology for Magnetic Soft Millirobots Navigating in Confined Spaces

Advanced Science, EarlyView.
A data‐efficient inverse design framework automates the optimization of magnetic soft millirobots for confined‐space navigation. Integrating a physics‐based Cosserat rod model with Bayesian optimization efficiently identifies high‐performance geometries.
Ziyu Ren, Hong Wang, Chak Wang Tse, Yi Zheng, Xi Chen, Wenqi Hu   +5 more
wiley   +1 more source

Neural Architecture Search Using Covariance Matrix Adaptation Evolution Strategy

Evolutionary Computation
Abstract Evolution-based neural architecture search methods have shown promising results, but they require high computational resources because these methods involve training each candidate architecture from scratch and then evaluating its fitness, which results in long search time. Covariance Matrix Adaptation Evolution Strategy (CMA-ES)
Nilotpal Sinha, Kuan-Wen Chen
openaire   +3 more sources

Improving Optimization with Gaussian Processes in the Covariance Matrix Adaptation Evolution Strategy. [PDF]

, 2023
This paper explores the use of Gaussian processes (GPs) in the covariance matrix adaptation evolution strategy (CMA-ES) for black-box optimization. GPs are powerful probabilistic models that capture complex relationships, making them suitable for modeling uncertain objective functions. Integrating GPs into the CMA-ES improves exploration and adaptation
Tumpach, J., Koza, J., Holeňa, M. (Martin)   +2 more
openaire   +1 more source