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This paper presents our computational methodology using Genetic Algorithms (GA) for exploring the nature of RNA editing. These models are constructed using several genetic editing characteristics that are gleaned from the RNA editing system…

Neural and Evolutionary Computing · Computer Science 2007-05-23 C. Huang , L. M. Rocha

One of the main limitations of utilizing optimal wavefront shaping in imaging and authentication applications is the slow speed of the optimization algorithms currently being used. To address this problem we develop a micro-genetic…

Photonic inverse design has emerged as an indispensable engineering tool for complex optical systems. In many instances it is important to optimize for both material and geometry configurations, which results in complex non-smooth search…

Optics · Physics 2021-06-17 Jagrit Digani , Phillip Hon , Artur R. Davoyan

Genetic Algorithms (GA) are a class of metaheuristic global optimization methods inspired by the process of natural selection among individuals in a population. Despite their widespread use, a comprehensive theoretical analysis of these…

Optimization and Control · Mathematics 2025-02-24 Giacomo Borghi , Lorenzo Pareschi

An optimal control approach based on multiple parameter genetic algorithms is applied to the design of plasmonic nanoconstructs with pre-determined optical properties and functionalities. We first develop nanoscale metallic lenses that…

Optics · Physics 2008-08-14 Joseph Yelk , Maxim Sukharev , Tamar Seideman

Genetic algorithms have played an important role in engineering optimization. Traditional GAs treat each gene separately. However, biophysical studies of gene regulatory networks revealed direct associations between different genes. It…

Neural and Evolutionary Computing · Computer Science 2024-05-01 Zhaoning Shi , Meng Xiang , Zhaoyang Hai , Xiabi Liu , Yan Pei

Solving Quadratic equation is one of the intrinsic interests as it is the simplest nonlinear equations. A novel approach for solving Quadratic Equation based on Genetic Algorithms (GAs) is presented. Genetic Algorithms (GAs) are a technique…

Neural and Evolutionary Computing · Computer Science 2013-06-20 Tanistha Nayak , Tirtharaj Dash

Quantum computing leverages the unique properties of qubits and quantum parallelism to solve problems intractable for classical systems, offering unparalleled computational potential. However, the optimization of quantum circuits remains…

We develop an accelerated Genetic Algorithm (GA) system constructed by the cooperation of field-programmable gate array (FPGA) and optimized parameters of the GA. We found the enhanced decay of mutation rate makes convergence of the GA much…

Image and Video Processing · Electrical Eng. & Systems 2022-10-05 Shu Guo , Lin Pang

The method and the advantages of an evolutionary computing based approach using a steady state genetic algorithm (GA) for the parameterization of interatomic potentials for metal oxides within the shell model framework are developed and…

Materials Science · Physics 2013-06-06 Jose Solomon , Peter Chung , Deepak Srivastava , Eric Darve

Topological photonic crystals (PCs) can support robust edge modes to transport electromagnetic energy in an efficient manner. Such edge modes are the eigenmodes of the PDE operator for a joint optical structure formed by connecting together…

Optimization and Control · Mathematics 2024-07-30 Chiu-Yen Kao , Junshan Lin , Braxton Osting

Recently, Smajic et al. published an article on numerical structural opti- mizations of two-dimensional photonic crystals using two different classes of optimization algorithms i.e, deterministic for local searches and stochastic for…

Other Condensed Matter · Physics 2007-05-23 Andreas Hakansson , Jose Sanchez-Dehesa

We present a Python package together with a practical guide for the implementation of a lightweight diversity-enhanced genetic algorithm (GA) approach for the exploration of multi-dimensional parameter spaces. Searching a parameter space…

Neural and Evolutionary Computing · Computer Science 2024-12-24 Jonas Wessén , Eliel Camargo-Molina

There have been extensive works dealing with genetic algorithms (GAs) for seeking optimal solutions of shop scheduling problems. Due to the NP hardness, the time cost is always heavy. With the development of high performance computing (HPC)…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-09 Jia Luo , Didier El Baz

Recently, researchers have applied genetic algorithms (GAs) to address some problems in quantum computation. Also, there has been some works in the designing of genetic algorithms based on quantum theoretical concepts and techniques. The so…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Gilson A. Giraldi , Renato Portugal , Ricardo N. Thess

In early-stage architectural design, optimization algorithms are essential for efficiently exploring large and complex design spaces under tight computational constraints. While prior research has benchmarked various optimization methods,…

Neural and Evolutionary Computing · Computer Science 2025-04-14 Farnaz Nazari , Wei Yan

We propose the use of the parallel tabu search algorithm (PTS) to solve combinatorial inverse design problems in integrated photonics. To assess the potential of this algorithm, we consider the problem of beam shaping using a…

Optics · Physics 2013-06-19 Denis Gagnon , Joey Dumont , Louis J. Dubé

We present a genetic algorithm (GA)-based inverse design framework for synthesizing high-performance planar terahertz (THz) filters integrated with coplanar striplines (CPSs). The method efficiently explores high-dimensional design spaces…

Applied Physics · Physics 2025-06-05 Ali Dehghanian , Thomas Darcie , Levi Smith

For simple digital circuits, conventional method of designing circuits can easily be applied. But for complex digital circuits, the conventional method of designing circuits is not fruitfully applicable because it is time-consuming. On the…

Neural and Evolutionary Computing · Computer Science 2013-04-10 S. M. Ashik Eftekhar , Sk. Mahbub Habib , M. M. A. Hashem

Convolutional Neural Networks (CNN) have gained great success in many artificial intelligence tasks. However, finding a good set of hyperparameters for a CNN remains a challenging task. It usually takes an expert with deep knowledge, and…

Neural and Evolutionary Computing · Computer Science 2020-06-25 Xueli Xiao , Ming Yan , Sunitha Basodi , Chunyan Ji , Yi Pan