scholarly journals Application of Optimization Algorithms in Clusters

2021 ◽  
Vol 9 ◽  
Author(s):  
Ruby Srivastava
Keyword(s):  
Genetic Algorithm ◽  
Evolutionary Algorithm ◽  
Potential Energy Surfaces ◽  
Optimization Algorithms ◽  
Computational Techniques ◽  
Geometrical Isomers ◽  
Immune Optimization ◽  
Accuracy Of Results ◽  
Basin Hopping ◽  
Energy Surfaces

The structural characterization of clusters or nanoparticles is essential to rationalize their size and composition-dependent properties. As experiments alone could not provide complete picture of cluster structures, so independent theoretical investigations are needed to find out a detail description of the geometric arrangement and corresponding properties of the clusters. The potential energy surfaces (PES) are explored to find several minima with an ultimate goal of locating the global minima (GM) for the clusters. Optimization algorithms, such as genetic algorithm (GA), basin hopping method and its variants, self-consistent basin-to-deformed-basin mapping, heuristic algorithm combined with the surface and interior operators (HA-SIO), fast annealing evolutionary algorithm (FAEA), random tunneling algorithm (RTA), and dynamic lattice searching (DLS) have been developed to solve the geometrical isomers in pure elemental clusters. Various model or empirical potentials (EPs) as Lennard–Jones (LJ), Born–Mayer, Gupta, Sutton–Chen, and Murrell–Mottram potentials are used to describe the bonding in different type of clusters. Due to existence of a large number of homotops in nanoalloys, genetic algorithm, basin-hopping algorithm, modified adaptive immune optimization algorithm (AIOA), evolutionary algorithm (EA), kick method and Knowledge Led Master Code (KLMC) are also used. In this review the optimization algorithms, computational techniques and accuracy of results obtained by using these mechanisms for different types of clusters will be discussed.

AI-BL1.0: a program for automatic on-line beamline optimization using the evolutionary algorithm

2017 ◽  
Vol 24 (1) ◽  
pp. 367-373 ◽  
Author(s):  
Shibo Xi ◽  
Lucas Santiago Borgna ◽  
Lirong Zheng ◽  
Yonghua Du ◽  
Tiandou Hu
Keyword(s):  
Genetic Algorithm ◽  
Synchrotron Radiation ◽  
Differential Evolution ◽  
Evolutionary Algorithm ◽  
Open Source ◽  
Light Source ◽  
Optimization Algorithms ◽  
Beijing Synchrotron Radiation Facility ◽  
On Line ◽  
Synchrotron Light

In this report, AI-BL1.0, an open-source Labview-based program for automatic on-line beamline optimization, is presented. The optimization algorithms used in the program are Genetic Algorithm and Differential Evolution. Efficiency was improved by use of a strategy known as Observer Mode for Evolutionary Algorithm. The program was constructed and validated at the XAFCA beamline of the Singapore Synchrotron Light Source and 1W1B beamline of the Beijing Synchrotron Radiation Facility.

Immune Programming Applications in Image Segmentation

2011 ◽  
pp. 304-321
Author(s):  
Xiaojun Bi
Keyword(s):  
Genetic Algorithm ◽  
Image Segmentation ◽  
Theoretical Analysis ◽  
Evolutionary Algorithm ◽  
Optimization Algorithms ◽  
Convergence Speed ◽  
Experimental Results ◽  
Intelligent Algorithms ◽  
Slow Convergence ◽  
Immune Programming

In fact, image segmentation can be regarded as a constrained optimization problem, and a series of optimization strategies can be used to complete the task of image segmentation. Traditional evolutionary algorithm represented by Genetic Algorithm is an efficient approach for image segmentation, but in the practical application, there are many problems such as the slow convergence speed of evolutionary algorithm and premature convergence, which have greatly constrained the application. The goal of introducing immunity into the existing intelligent algorithms is to utilize some characteristics and knowledge in the pending problems for restraining the degenerative phenomena during evolution so as to improve the algorithmic efficiency. Theoretical analysis and experimental results show that immune programming outperforms the existing optimization algorithms in global convergence speed and is conducive to alleviating the degeneration phenomenon. Theoretical analysis and experimental results show that immune programming has better global optimization and outperforms the existing optimization algorithms in alleviating the degeneration phenomenon. It is a feasible and effective method of image segmentation.

scholarly journals X-ray emission spectroscopy: a genetic algorithm to disentangle core–hole-induced dynamics

2021 ◽  
Vol 140 (12) ◽  
Author(s):  
Lars G. M. Pettersson ◽  
Osamu Takahashi
Keyword(s):  
Genetic Algorithm ◽  
Cross Sections ◽  
Potential Energy Surfaces ◽  
Water Clusters ◽  
Life Time ◽  
Core Hole ◽  
Final State ◽  
X Ray ◽  
State Potential ◽  
Energy Surfaces

AbstractA genetic algorithm (GA) is developed and applied to make proper connections of final-state potential-energy surfaces and X-ray emission (XES) cross sections between steps in the time-propagation of H-bonded systems after a core–hole is created. We show that this modification results in significantly improved resolution of spectral features in XES with the semiclassical Kramers–Heisenberg approach which takes into account important interference effects. We demonstrate the effects on a water pentamer model as well as on two 17-molecules water clusters representing, respectively, tetrahedral (D2A2) and asymmetric (D1A1) H-bonding environments. For D2A2, the applied procedure improves significantly the obtained intensities, whereas for D1A1 the effects are smaller due to milder dynamics during the core–hole life-time as only one hydrogen is involved. We reinvestigate XES for liquid ethanol and, by properly disentangling the relevant states in the dense manifold of states using the GA, now resolve the important 3a′′ state as a peak rather than a shoulder. Furthermore, by applying the SpecSwap-RMC procedure, we reweigh the distribution of structures in the sampling of the liquid to fit to experiment and estimate the ratio between the main anti and gauche conformers in the liquid at room temperature. This combination of techniques will be generally applicable to challenging problems in liquid-phase spectroscopy.

Exploring potential energy surfaces of biological molecules using a Multi-Niche Crowding genetic algorithm

2017 ◽  
Vol 17 (3) ◽  
pp. 595-609
Author(s):  
Anouar El Guerdaoui ◽  
Rachida Tijar ◽  
Brahim El Merbouh ◽  
Malika Bourjila ◽  
Rachid Drissi El Bouzaidi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Potential Energy ◽  
Potential Energy Surfaces ◽  
Biological Molecules ◽  
Energy Surfaces

Resolving the Quadruple Bonding Conundrum in C2 Using Insights Derived from Excited State Potential Energy Surfaces: A Molecular Orbital Perspective

2019 ◽  
Author(s):  
Ishita Bhattacharjee ◽  
Debashree Ghosh ◽  
Ankan Paul
Keyword(s):  
Excited State ◽  
Potential Energy ◽  
Molecular Orbital ◽  
High Spin ◽  
Potential Energy Surfaces ◽  
Valence Bond ◽  
Deep Minimum ◽  
State Potential ◽  
Energy Surfaces ◽  
Mo Theory

The question of quadruple bonding in C<sub>2</sub> has emerged as a hot button issue, with opinions sharply divided between the practitioners of Valence Bond (VB) and Molecular Orbital (MO) theory. Here, we have systematically studied the Potential Energy Curves (PECs) of low lying high spin sigma states of C<sub>2</sub>, N<sub>2</sub> and Be<sub>2</sub> and HC≡CH using several MO based techniques such as CASSCF, RASSCF and MRCI. The analyses of the PECs for the<sup> 2S+1</sup>Σ<sub>g/u</sub> (with 2S+1=1,3,5,7,9) states of C<sub>2</sub> and comparisons with those of relevant dimers and the respective wavefunctions were conducted. We contend that unlike in the case of N<sub>2</sub> and HC≡CH, the presence of a deep minimum in the <sup>7</sup>Σ state of C<sub>2</sub> and CN<sup>+</sup> suggest a latent quadruple bonding nature in these two dimers. Hence, we have struck a reconciliatory note between the MO and VB approaches. The evidence provided by us can be experimentally verified, thus providing the window so that the narrative can move beyond theoretical conjectures.

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