23 papers · ranked by Valyu relevance
Peng Su, Yuxin Zhao, Xiaobo Li, Zhendi Ma + 3 more
'Changsheng Zhang' 'Haitong Zhao'] As modern medical technology advances, the utilization of gene expression data has proliferated across diverse domains, particularly in cancer diagnosis and prognosis monitoring. However, gene expression data is often characterized by high dimensionality and a prevalence of redundant…
An-Di Tang, Tong Han, Huan Zhou, Lei Xie
The unmanned aerial vehicle (UAV) path planning problem is a type of complex multi-constraint optimization problem that requires a reasonable mathematical model and an efficient path planning algorithm. In this paper, the fitness function including fuel consumption cost, altitude cost, and threat cost is established.…
Yu Li, Xiao Liang, Jingsen Liu, Huan Zhou + 1 more
The Equilibrium Optimizer (EO) is a recently proposed intelligent optimization algorithm based on mass balance equation. It has a novel principle to deal with global optimization. However, when solving complex numerical optimization problems and engineering problems, the algorithm will get stuck into local optima and…
Tansel Dökeroğlu, Deniz Canturk, Tayfun Küçükyılmaz
This review examines over 150 new metaheuristics of the last six years (between 2019-2024), underscoring their profound influence and performance. Over the past three decades, more than 500 new metaheuristic algorithms have been proposed, with no slowdown in sight—an overwhelming abundance that complicates the process…
Essam H. Houssein, Gamela Nageh, Mohamed Abd Elaziz, Eman Younis + 1 more
'Chan Hwang See'] The use of solar photovoltaic systems (PVs) is increasing as a clean and affordable source of electric energy. The Pv cell is the main component of the PV system. To improve the performance, control, and evaluation of the PV system, it is necessary to provide accurate design and to define the…
Hao Chen, Weikun Li, Weicheng Cui
Nature-inspired computing has attracted huge attention since its origin, especially in the field of multiobjective optimization. This paper proposes a disruption-based multiobjective equilibrium optimization algorithm (DMOEOA). A novel mutation operator named layered disruption method is integrated into the proposed…
Djemai Charef-Khodja, Abida Toumi
—Multiple objects tracking (MOT) is a difficult task, as it usually requires special hardware and higher computation complexity. In this work, we present a new framework of MOT by using of equilibrium optimizer (EO) algorithm and reducing the resolution of the bounding boxes of the objects to solve such problems in the…
Oguz Emrah Turgut, Hadi Genceli, Mustafa Asker, Mustafa Turhan Çoban + 1 more
'Mohammad Akrami'] This study proposes a Hierarchical Manta-Ray Foraging Optimization (HMRFO) algorithm for calculating the equilibrium points of chemical reactions. To improve the solution diversity in the trial Manta-Ray population and enhance the general optimization effectivity of the algorithm, an ordered…
Rory Conlin, Patrick Kim, Daniel W. Dudt, Dario Panici + 1 more
'Egemen Kolemen'] In this work we consider the problem of optimizing a stellarator subject to hard constraints on the design variables and physics properties of the equilibrium. We survey current numerical methods for handling these constraints, and summarize a number of methods from the wider optimization community…
Vahid Mardanlou, Elisa Franco
In a synthetic biological network it may often be desirable to maximize or minimize parameters such as reaction rates, fluxes and total concentrations of reagents, while preserving a given dynamic behavior. We consider the problem of parameter optimization in biomolecular bistable circuits. We show that, under some…
Varun Ojha, Bartolomeo Pantò, Giuseppe Nicosia
The paper proposes a novel adaptive search space decomposition method and a novel gradient-free optimization-based formulation for the pre- and post-buckling analyses of space truss structures. Space trusses are often employed in structural engineering to build large steel constructions, such as bridges and domes…
Sergei V. Krivov
We extend the non-parametric framework of reaction coordinate optimization to non-equilibrium ensembles of (short) trajectories. For example, we show how, starting from such an ensemble, one can obtain an equilibrium free energy profile along the committor, which can be used to determine important properties of the…
Eric Hermes, Khachik Sargsyan, Habib Najm, Judit Zádor
We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, e.g. through the…
Akhil Shajan, Madushanka Manathunga, Andreas Goetz, Kenneth Merz
Based on a series of energy minimizations with starting structures obtained from the Baker test set of 30 organic molecules, a comparison is made between various open source geometry optimization codes that are interfaced with the open-source QUantum Interaction Computational Kernel (QUICK) program for gradient and…
Akhil Shajan, Madushanka Manathunga, Andreas Goetz, Kenneth Merz
Based on a series of energy minimizations with starting structures obtained from the Baker test set of 30 organic molecules, a comparison is made between various open- source geometry optimization codes that are interfaced with the open-source QUantum Interaction Computational Kernel (QUICK) program for gradient and…
Caio Felippe Curitiba Marcellos, Gerson Francisco da Silva, Ilka do Amaral Soares, Fábio Ramos + 1 more
'Ilka do Amaral Soares' 'Fábio Ramos' 'Evaristo C. Biscaia'] In several industrial applications, such as crystallization, pollution control, and flow assurance, an accurate understanding of the aqueous electrolyte solutions is crucial. Electrolyte equilibrium calculation contributes with the design and optimization of…
Philippe A. Robert, Henrik Jönsson, Michael Meyer-Hermann
The modelling of biological systems often consists into differential equation models that need to be fitted to experimental data. During this complex process, the practical experience of the biologist and the theoretical abstraction of the modeller require back-and-forth refinements of the model, design of new…
AKHIL SHAJAN, Madushanka Manathunga, Andreas Goetz, Kenneth Merz
Based on a series of energy minimizations with starting structures obtained from the Baker test set of 30 organic molecules, a comparison is made between various open-source geometry optimization codes that are interfaced with the open-source QUantum Interaction Computational Kernel (QUICK) program for gradient and…
Kazunori D Yamada
In the deep learning era, a gradient descent method is the most common method to optimize parameters of neural networks. Among various mathematical optimization methods, a gradient descent method is the most naive method. Although controlling a learning rate of the method is necessary for quick convergence, the…
Adithya Sagar, Rachel LeCover, Christine Shoemaker, Jeffrey Varner
Mathematical modeling is a powerful tool to analyze, and ultimately design biochemical networks. However, the estimation of the parameters that appear in biochemical models is a significant challenge. Parameter estimation typically involves expensive function evaluations and noisy data, making it difficult to quickly…
Alejandro F. Villaverde, Fabian Fröhlich, Daniel Weindl, Jan Hasenauer + 1 more
Mechanistic kinetic models usually contain unknown parameters, which need to be estimated by optimizing the fit of the model to experimental data. This task can be computationally challenging due to the presence of local optima and ill-conditioning. While a variety of optimization methods have been suggested to…
Fabian Fröhlich, Peter K. Sorger
Ordinary differential equation (ODE) models are widely used to describe biochemical processes, since they effectively represent mass action kinetics. Optimization-based calibration of ODE models on experimental data can be challenging, even for low-dimensional problems. However, reliable model calibration is a…
Authors not listed
Designing efficient photoreactors remains challenging due to the complex interplay of light transport phenomena, shaped by reflection, scattering and absorption processes. Here, we introduce a workflow that integrates ray-tracing digital twins with multi-objective Bayesian optimization to autonomously design…