A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Growth, Optical Properties and Applications of Thin Film Diamond

Diamond’s chemical inertness and high transparency over a wide wavelength range makes it ideal for many optical applications. However, one of the drawbacks of using diamond is that 29% of the incident light is reflected and so additional methods must be used to increase or alter the transmission properties. One technique that achieves this is by coating the optical component with another material with a suitable refractive index. Recent developments in the synthesis of diamond using plasma enhanced chemical vapour deposition have allowed the fabrication of relatively uniform and pinhole free thin films making it possible to use it as part of an optical system. However, the method of deposition makes it difficult to incorporate into standard processes where multiple layers of different materials are required. In this thesis, the optical properties of thin membranes made of nanocrystalline diamond are evaluated and modified by coating the membranes with dielectric layers. Applications of these composite films are examined as part of a tunable lens, where the deformable membrane that adjusts the focal length is made of a double layer antireflection coating, to increase the transmission at a set wavelength. Additionally, the use of these membranes as very thin beam splitters has been explored and measurements taken to show how these components can be used to modify the polarisation state of the transmitted and reflected light. Ways to determine more complicated coating structures are then examined and some novel coating structures are presented which could be used to coat a diamond optical component

The discovery of new functional oxides using combinatorial techniques and advanced data mining algorithms

Electroceramic materials research is a wide ranging field driven by device applications. For many years, the demand for new materials was addressed largely through serial processing and analysis of samples often similar in composition to those already characterised. The Functional Oxide Discovery project (FOXD) is a combinatorial materials discovery project combining high-throughput synthesis and characterisation with advanced data mining to develop novel materials. Dielectric ceramics are of interest for use in telecommunications equipment; oxygen ion conductors are examined for use in fuel cell cathodes. Both applications are subject to ever increasing industry demands and materials designs capable of meeting the stringent requirements are urgently required. The London University Search Instrument (LUSI) is a combinatorial robot employed for materials synthesis. Ceramic samples are produced automatically using an ink-jet printer which mixes and prints inks onto alumina slides. The slides are transferred to a furnace for sintering and transported to other locations for analysis. Production and analysis data are stored in the project database. The database forms a valuable resource detailing the progress of the project and forming a basis for data mining. Materials design is a two stage process. The first stage, forward prediction, is accomplished using an artificial neural network, a Baconian, inductive technique. In a second stage, the artificial neural network is inverted using a genetic algorithm. The artificial neural network prediction, stoichiometry and prediction reliability form objectives for the genetic algorithm which results in a selection of materials designs. The full potential of this approach is realised through the manufacture and characterisation of the materials. The resulting data improves the prediction algorithms, permitting iterative improvement to the designs and the discovery of completely new materials

SCEE 2008 book of abstracts : the 7th International Conference on Scientific Computing in Electrical Engineering (SCEE 2008), September 28 – October 3, 2008, Helsinki University of Technology, Espoo, Finland

This report contains abstracts of presentations given at the SCEE 2008 conference.reviewe

Efficiency and Optimization of Buildings Energy Consumption: Volume II

This reprint, as a continuation of a previous Special Issue entitled “Efficiency and Optimization of Buildings Energy Consumption”, gives an up-to-date overview of new technologies based on Machine Learning (ML) and Internet of Things (IoT) procedures to improve the mathematical approach of algorithms that allow control systems to be improved with the aim of reducing housing sector energy consumption

An effective optimisation method for multifactor and reliability-related structural design problems

This thesis first presents a systematic design procedure which satisfies the required strength and stiffness, and structural mass for conceptual engineering structural designs. The procedure employs a multi-objective and multi-disciplinary (MO–MD) optimisation method (multifactor optimisation of structure techniques, MOST) which is coupled with finite element analysis (FEA) as an analysis tool for seeking the optimum design. The effectiveness of the MOST technique is demonstrated in two case studies.Next, a reliability-related multi-factor optimisation method is proposed and developed, representing a combination of MOST (as a method of multi-factor optimisation) and the reliability-loading case index (RLI) (as a method of calculating the reliability index). The RLI is developed based on a well-known reliability method: the first-order reliability method (FORM). The effectiveness and robustness of the proposed methodology are demonstrated in two case studies in which the method is used to simultaneously consider multi-objective, multi-disciplinary, and multi-loading-case problems. The optimised designs meet the targeted performance criteria under various loading conditions.The results show that the attributes of the proposed optimisation methods can be used to address engineering design problems which require simultaneous consideration of multi-disciplinary problems. An important contribution of this study is the development of a conceptual MO–MD design optimisation method, in which multi-factor structural and reliability design problems can be simultaneously considered

Optimization Methods Applied to Power Systems Ⅱ

Electrical power systems are complex networks that include a set of electrical components that allow distributing the electricity generated in the conventional and renewable power plants to distribution systems so it can be received by final consumers (businesses and homes). In practice, power system management requires solving different design, operation, and control problems. Bearing in mind that computers are used to solve these complex optimization problems, this book includes some recent contributions to this field that cover a large variety of problems. More specifically, the book includes contributions about topics such as controllers for the frequency response of microgrids, post-contingency overflow analysis, line overloads after line and generation contingences, power quality disturbances, earthing system touch voltages, security-constrained optimal power flow, voltage regulation planning, intermittent generation in power systems, location of partial discharge source in gas-insulated switchgear, electric vehicle charging stations, optimal power flow with photovoltaic generation, hydroelectric plant location selection, cold-thermal-electric integrated energy systems, high-efficiency resonant devices for microwave power generation, security-constrained unit commitment, and economic dispatch problems

Air Force Institute of Technology Research Report 2007

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics