13 research outputs found
A solution to the crucial problem of population degeneration in high-dimensional evolutionary optimization
Three popular evolutionary optimization algorithms are tested on high-dimensional benchmark functions. An important phenomenon responsible for many failures - population degeneration - is discovered. That is, through evolution, the population of searching particles degenerates into a subspace of the search space, and the global optimum is exclusive from the subspace. Subsequently, the search will tend to be confined to this subspace and eventually miss the global optimum. Principal components analysis (PCA) is introduced to discover population degeneration and to remedy its adverse effects. The experiment results reveal that an algorithm's efficacy and efficiency are closely related to the population degeneration phenomenon. Guidelines for improving evolutionary algorithms for high-dimensional global optimization are addressed. An application to highly nonlinear hydrological models demonstrates the efficacy of improved evolutionary algorithms in solving complex practical problems. 漏 2011 IEEE
A convergence proof for the particle swarm optimiser
The Particle Swarm Optimiser (PSO) is a population based stochastic optimisation algorithm,
empirically shown to be efficient and robust. This paper provides a proof to show that the
original PSO does not have guaranteed convergence to a local optimum. A flaw in the original PSO
is identified which causes stagnation of the swarm. Correction of this flaw results in a PSO algorithm
with guaranteed convergence to a local minimum. Further extensions with provable global
convergence are also described. Experimental results are provided to elucidate the behavior of the
modified PSO as well as PSO variations with global convergence.http://www.iospress.nl/loadtop/load.php?isbn=0169296
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1996 Laboratory directed research and development annual report
This report summarizes progress from the Laboratory Directed Research and Development (LDRD) program during fiscal year 1996. In addition to a programmatic and financial overview, the report includes progress reports from 259 individual R&D projects in seventeen categories. The general areas of research include: engineered processes and materials; computational and information sciences; microelectronics and photonics; engineering sciences; pulsed power; advanced manufacturing technologies; biomedical engineering; energy and environmental science and technology; advanced information technologies; counterproliferation; advanced transportation; national security technology; electronics technologies; idea exploration and exploitation; production; and science at the interfaces - engineering with atoms
Micro/Nano Structures and Systems
Micro/Nano Structures and Systems: Analysis, Design, Manufacturing, and Reliability is a comprehensive guide that explores the various aspects of micro- and nanostructures and systems. From analysis and design to manufacturing and reliability, this reprint provides a thorough understanding of the latest methods and techniques used in the field. With an emphasis on modern computational and analytical methods and their integration with experimental techniques, this reprint is an invaluable resource for researchers and engineers working in the field of micro- and nanosystems, including micromachines, additive manufacturing at the microscale, micro/nano-electromechanical systems, and more. Written by leading experts in the field, this reprint offers a complete understanding of the physical and mechanical behavior of micro- and nanostructures, making it an essential reference for professionals in this field
Optimizaci贸n metaheur铆stica para la planificaci贸n de redes WDM
Las implementaciones actuales de las redes de telecomunicaciones no permiten soportar el incremento en la demanda de ancho de banda producido por el crecimiento del tr谩fico de datos en las 煤ltimas d茅cadas. La aparici贸n de la fibra 贸ptica y el desarrollo de la tecnolog铆a de multiplexaci贸n por divisi贸n de longitudes de onda (WDM) permite incrementar la capacidad de redes de telecomunicaciones existentes mientras se minimizan costes. En este trabajo se planifican redes 贸pticas WDM mediante la resoluci贸n de los problemas de Provisi贸n y Conducci贸n en redes WDM (Provisioning and Routing Problem) y de Supervivencia (Survivability Problem). El Problema de Conducci贸n y Provisi贸n consiste en incrementar a m铆nimo coste la capacidad de una red existente de tal forma que se satisfaga un conjunto de requerimientos de demanda. El problema de supervivencia consiste en garantizar el flujo del tr谩fico a trav茅s de una red en caso de fallo de alguno de los elementos de la misma. Adem谩s se resuelve el Problema de Provisi贸n y Conducci贸n en redes WDM con incertidumbre en las demandas. Para estos problemas se proponen modelos de programaci贸n lineal entera. Las metaheur铆sticas proporcionan un medio para resolver problemas de optimizaci贸n complejos, como los que surgen al planificar redes de telecomunicaciones, obteniendo soluciones de alta calidad en un tiempo computacional razonable. Las metaheur铆sticas son estrategias que gu铆an y modifican otras heur铆sticas para obtener soluciones m谩s all谩 de las generadas usualmente en la b煤squeda de optimalidad local. No garantizan que la mejor soluci贸n encontrada, cuando se satisfacen los criterios de parada, sea una soluci贸n 贸ptima global del problema. Sin embargo, la experimentaci贸n de implementaciones metaheur铆sticas muestra que las estrategias de b煤squeda embebidas en tales procedimientos son capaces de encontrar soluciones de alta calidad a problemas dif铆ciles en industria, negocios y ciencia. Para la soluci贸n del problema de Provisi贸n y Conducci贸n en Redes WDM, se desarrolla un algoritmo metaheur铆stico h铆brido que combina principalmente ideas de las metaheur铆sticas B煤squeda Dispersa (Scatter Search) y B煤squeda Mutiarranque (Multistart). Adem谩s a帽ade una componente tab煤 en uno de los procedimiento del algoritmo. Se utiliza el modelo de programaci贸n lineal entera propuesto por otros autores y se propone un modelo de programaci贸n lineal entera alternativo que proporciona cotas superiores al problema, pero incluye un menor n煤mero de variables y restricciones, pudiendo ser resuelto de forma 贸ptima para tama帽os de red mayores. Los resultados obtenidos por el algoritmo metaheur铆stico dise帽ado se comparan con los obtenidos por un procedimiento basado en permutaciones de las demandas propuesto anteriormente por otros autores, y con los dos modelos de programaci贸n lineal entera usados. Se propone modelos de programaci贸n lineal entera para sobrevivir la red en caso de fallos en un 煤nico enlace. Se proponen modelos para los esquemas de protecci贸n de enlace compartido, de camino compartido con enlaces disjuntos, y de camino compartido sin enlaces disjuntos. Se propone un m茅todo de resoluci贸n metaheur铆stico que obtiene mejores costes globales que al resolver el problema en dos fases, es decir, al resolver el problema de servicio y a continuaci贸n el de supervivencia. Se proponen adem谩s modelos de programaci贸n entera para resolver el problema de provisi贸n en redes WDM con incertidumbres en las demandas
MEMS Accelerometers
Micro-electro-mechanical system (MEMS) devices are widely used for inertia, pressure, and ultrasound sensing applications. Research on integrated MEMS technology has undergone extensive development driven by the requirements of a compact footprint, low cost, and increased functionality. Accelerometers are among the most widely used sensors implemented in MEMS technology. MEMS accelerometers are showing a growing presence in almost all industries ranging from automotive to medical. A traditional MEMS accelerometer employs a proof mass suspended to springs, which displaces in response to an external acceleration. A single proof mass can be used for one- or multi-axis sensing. A variety of transduction mechanisms have been used to detect the displacement. They include capacitive, piezoelectric, thermal, tunneling, and optical mechanisms. Capacitive accelerometers are widely used due to their DC measurement interface, thermal stability, reliability, and low cost. However, they are sensitive to electromagnetic field interferences and have poor performance for high-end applications (e.g., precise attitude control for the satellite). Over the past three decades, steady progress has been made in the area of optical accelerometers for high-performance and high-sensitivity applications but several challenges are still to be tackled by researchers and engineers to fully realize opto-mechanical accelerometers, such as chip-scale integration, scaling, low bandwidth, etc
MEMS Technology for Biomedical Imaging Applications
Biomedical imaging is the key technique and process to create informative images of the human body or other organic structures for clinical purposes or medical science. Micro-electro-mechanical systems (MEMS) technology has demonstrated enormous potential in biomedical imaging applications due to its outstanding advantages of, for instance, miniaturization, high speed, higher resolution, and convenience of batch fabrication. There are many advancements and breakthroughs developing in the academic community, and there are a few challenges raised accordingly upon the designs, structures, fabrication, integration, and applications of MEMS for all kinds of biomedical imaging. This Special Issue aims to collate and showcase research papers, short commutations, perspectives, and insightful review articles from esteemed colleagues that demonstrate: (1) original works on the topic of MEMS components or devices based on various kinds of mechanisms for biomedical imaging; and (2) new developments and potentials of applying MEMS technology of any kind in biomedical imaging. The objective of this special session is to provide insightful information regarding the technological advancements for the researchers in the community
Swarm intelligence and its applications to wireless ad hoc and sensor networks.
Swarm intelligence, as inspired by natural biological swarms, has numerous powerful
properties for distributed problem solving in complex real world applications such
as optimisation and control. Swarm intelligence properties can be found in natural
systems such as ants, bees and birds, whereby the collective behaviour of unsophisticated
agents interact locally with their environment to explore collective problem solving
without centralised control. Recent advances in wireless communication and digital
electronics have instigated important changes in distributed computing. Pervasive
computing environments have emerged, such as large scale communication networks
and wireless ad hoc and sensor networks that are extremely dynamic and unreliable.
The network management and control must be based on distributed principles where
centralised approaches may not be suitable for exploiting the enormous potential of
these environments. In this thesis, we focus on applying swarm intelligence to the
wireless ad hoc and sensor networks optimisation and control problems.
Firstly, an analysis of the recently proposed particle swarm optimisation, which is
based on the swarm intelligence techniques, is presented. Previous stability analysis
of the particle swarm optimisation was restricted to the assumption that all of the
parameters are non random since the theoretical analysis with the random parameters
is difficult. We analyse the stability of the particle dynamics without these restrictive
assumptions using Lyapunov stability and passive systems concepts. The particle
swarm optimisation is then used to solve the sink node placement problem in sensor
networks.
Secondly, swarm intelligence based routing methods for mobile ad hoc networks
are investigated. Two protocols have been proposed based on the foraging behaviour
of biological ants and implemented in the NS2 network simulator. The first protocol
allows each node in the network to choose the next node for packets to be
forwarded on the basis of mobility influenced routing table. Since mobility is one of
the most important factors for route changes in mobile ad hoc networks, the mobility
of the neighbour node using HELLO packets is predicted and then translated into a
pheromone decay as found in natural biological systems. The second protocol uses
the same mechanism as the first, but instead of mobility the neighbour node remaining
energy level and its drain rate are used. The thesis clearly shows that swarm
intelligence methods have a very useful role to play in the management and control
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problems associated with wireless ad hoc and sensor networks. This thesis has given
a number of example applications and has demonstrated its usefulness in improving
performance over other existing methods