Particle swarm optimization: the gradient correction

In the following paper, the solution of the optimization problem that relied on the determination of the optimal geometry of two cylindrical coil arrangement evoking magnetic field of specific parameters was presented. The objective of the task was to generate, in a defined active area, the magnetic field of the largest possible gradient and simultaneously keep this gradient relatively constant. The computations were performed using the classical particle swarm optimization as well as the modified method with the correction sensitive to the fitness function gradient introduced to the formula describing the movement of the specific swarm particles. As a result, a considerable enhancement of the optimization process was achieved

Stochastics global optimization methods and their applications in Chemical Engineering

Ph.DDOCTOR OF PHILOSOPH

Multidisciplinary Design Optimization for Space Applications

Multidisciplinary Design Optimization (MDO) has been increasingly studied in aerospace engineering with the main purpose of reducing monetary and schedule costs. The traditional design approach of optimizing each discipline separately and manually iterating to achieve good solutions is substituted by exploiting the interactions between the disciplines and concurrently optimizing every subsystem. The target of the research was the development of a flexible software suite capable of concurrently optimizing the design of a rocket propellant launch vehicle for multiple objectives. The possibility of combining the advantages of global and local searches have been exploited in both the MDO architecture and in the selected and self developed optimization methodologies. Those have been compared according to computational efficiency and performance criteria. Results have been critically analyzed to identify the most suitable optimization approach for the targeted MDO problem

Educational Simulator for Teaching of Particle Swarm Optimization in LabVIEW

This paper presents an educational software tool for aid the teaching of Particle Swarm Optimization (PSO) fundamentals with friendly design interface. This software were developed in the platform of LabVIEW (Laboratory Virtual Intrumentation Engineering Workbench). The software‟s best qualities are users can select many different version of the PSO algorithm, a lot of the benchmarks test functions for optimization and set the parameters that have an influence on the PSO performance. Through visualization of particle distribution in the searching, the simulator is particularly effective in providing users with an intuitive feel for the PSO algorithm

Review : Deep learning in electron microscopy

Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy

Unconstrained Global Optimization of Molecules on Surfaces: From globally optimized structures to scanning-probe data

The adsorption of molecules on a surface plays a vital role in heterogeneous catalysis. For a proper unterstanding of the reaction mechanisms involved, the adsorption ge ometry of the molecules on the surface needs to be known. So far, experimental data from tunneling microscopes and spectroscopy, such as STM and IRAS are the main ways to obtain such knowledge. Due to the vast search space of adsorption geometries, especially for oligomers, optimizations using ab initio methods can be used to confirm the experimental data only if good initial guesses are available. Global optimization can serve two purposes in these situations. On the one hand it allows for a thorough investigation of the given search space, which can provide good initial guesses for subsequent high-level structural refinements. On the other hand, given a known reaction mechanism, it could also be used to find catalysts that influence e.g. the relevant bonds. With respect to this idea the topic of this thesis is to find a local optimization method cheap enough such that the total computational cost of global optimization does not exceed availability and yet good enough that the results are meaningful to the problem at hand. With this in mind multiple force field and semiempirical methods have been tested and evaluated mainly on benzene, acetophenone and ethyl pyruvate on Pt(111) surfaces. Some other adsorbates have also been tested shortly. In addition to these global optimization results, DFT geometry optimizations of ethyl pyruvate on Pt(111) have been performed and the structures of the best adsorption geometry from global optimization and from DFT are compared. Furthermore, from the DFT data STM images have been calculated that are compared to experimental results. The theoretical and experimental STM images agree well

New Strategies for Global Optimization of Chemical Engineering Applications by Differential Evolution

Ph.DDOCTOR OF PHILOSOPH

Center for Space Microelectronics Technology

The 1990 technical report of the Jet Propulsion Laboratory Center for Space Microelectronics Technology summarizes the technical accomplishments, publications, presentations, and patents of the center during 1990. The report lists 130 publications, 226 presentations, and 87 new technology reports and patents