Optimization Methods (optimization + methods)

Distribution by Scientific Domains

Kinds of Optimization Methods

  • global optimization methods


  • Selected Abstracts


    Determination of Materials Selection Performance Indices Through the Combination of Numerical Modeling and Optimization Methods

    ADVANCED ENGINEERING MATERIALS, Issue 11 2009
    German Castillo
    After translation, the first stages traditionally involved in the materials selection are filtration and classification, which require formulation of criteria (constraints or objectives) deduced from information written in the set of material requirements. These criteria, which are representative of the behavior of the material and the studied structure, must be formulated analytically in order to be used during selection stage. However, for complex behavior, analytical processing of models is no longer possible and it can be replaced by a combination of numerical resolution methods and an optimization method which make it possible to obtain approximate formal expressions of the criteria. In this paper, a complete selection method is proposed. The method is applied to the constraints as well as the objectives, in order to carry out the filtration and classification stages at the same time. The study of the thermomechanical behavior of a machine tool frame has been used to demonstrate the validity of the proposed method. [source]


    User-Controllable Color Transfer

    COMPUTER GRAPHICS FORUM, Issue 2 2010
    Xiaobo An
    This paper presents an image editing framework where users use reference images to indicate desired color edits. In our approach, users specify pairs of strokes to indicate corresponding regions in both the original and the reference image that should have the same color "style". Within each stroke pair, a nonlinear constrained parametric transfer model is used to transfer the reference colors to the original. We estimate the model parameters by matching color distributions, under constraints that ensure no visual artifacts are present in the transfer result. To perform transfer on the whole image, we employ optimization methods to propagate the model parameters defined at each stroke location to spatially-close regions of similar appearance. This stroke-based formulation requires minimal user effort while retaining the high degree of user control necessary to allow artistic interpretations. We demonstrate our approach by performing color transfer on a number of image pairs varying in content and style, and show that our algorithm outperforms state-of-the-art color transfer methods on both user-controllability and visual qualities of the transfer results. [source]


    Optimization of integrated Earth System Model components using Grid-enabled data management and computation

    CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 2 2007
    A. R. Price
    Abstract In this paper, we present the Grid enabled data management system that has been deployed for the Grid ENabled Integrated Earth system model (GENIE) project. The database system is an augmented version of the Geodise Database Toolbox and provides a repository for scripts, binaries and output data in the GENIE framework. By exploiting the functionality available in the Geodise toolboxes we demonstrate how the database can be employed to tune parameters of coupled GENIE Earth System Model components to improve their match with observational data. A Matlab client provides a common environment for the project Virtual Organization and allows the scripting of bespoke tuning studies that can exploit multiple heterogeneous computational resources. We present the results of a number of tuning exercises performed on GENIE model components using multi-dimensional optimization methods. In particular, we find that it is possible to successfully tune models with up to 30 free parameters using Kriging and Genetic Algorithm methods. Copyright © 2006 John Wiley & Sons, Ltd. [source]


    Fossils provide better estimates of ancestral body size than do extant taxa in fishes

    ACTA ZOOLOGICA, Issue 2009
    James S. Albert
    Abstract The use of fossils in studies of character evolution is an active area of research. Characters from fossils have been viewed as less informative or more subjective than comparable information from extant taxa. However, fossils are often the only known representatives of many higher taxa, including some of the earliest forms, and have been important in determining character polarity and filling morphological gaps. Here we evaluate the influence of fossils on the interpretation of character evolution by comparing estimates of ancestral body size in fishes (non-tetrapod craniates) from two large and previously unpublished datasets; a palaeontological dataset representing all principal clades from throughout the Phanerozoic, and a macroecological dataset for all 515 families of living (Recent) fishes. Ancestral size was estimated from phylogenetically based (i.e. parsimony) optimization methods. Ancestral size estimates obtained from analysis of extant fish families are five to eight times larger than estimates using fossil members of the same higher taxa. These disparities arise from differential survival of large-bodied members of early branching lineages, and are not statistical or taphonomic artefacts. Estimates of ancestral size obtained from a limited but judicious selection of fossil fish taxa are more accurate than estimates from a complete dataset of extant fishes. [source]


    Development of an Expert System Shell Based on Genetic Algorithms for the Selection of the Energy Best Available Technologies and their Optimal Operating Conditions for the Process Industry

    EXPERT SYSTEMS, Issue 3 2001
    D.A. Manolas
    The development of genetic algorithms started almost three decades ago in an attempt to imitate the mechanics of natural systems. Since their inception, they have been applied successfully as optimization methods, and as expert systems, in many diverse applications. In this paper, a genetic-algorithm-based expert system shell is presented that, when combined with a proper database comprising the available energy-saving technologies for the process industry, is able to perform the following tasks: (a) identify the best available technologies (BATs) among the available ones for a given process industry, and (b) calculate their optimal design parameters in such a way that they comply with the energy requirements of the process. By the term BAT is meant the available energy-saving technology, among the existing ones in the market, that is the best for the case. [source]


    Iterative resolution estimation in least-squares Kirchhoff migration

    GEOPHYSICAL PROSPECTING, Issue 6 2002
    Sergey Fomel
    ABSTRACT We apply iterative resolution estimation to least-squares Kirchhoff migration. Reviewing the theory of iterative optimization uncovers the common origin of different optimization methods. This allows us to reformulate the pseudo-inverse, model resolution and data resolution operators in terms of effective iterative estimates. When applied to Kirchhoff migration, plots of the diagonal of the model resolution matrix reveal low illumination areas on seismic images and provide information about image uncertainties. Synthetic and real data examples illustrate the proposed technique and confirm the theoretical expectations. [source]


    Parameter identification for leaky aquifers using global optimization methods

    HYDROLOGICAL PROCESSES, Issue 7 2007
    Hund-Der Yeh
    Abstract In the past, graphical or computer methods were usually employed to determine the aquifer parameters of the observed data obtained from field pumping tests. Since we employed the computer methods to determine the aquifer parameters, an analytical aquifer model was required to estimate the predicted drawdown. Following this, the gradient-type approach was used to solve the nonlinear least-squares equations to obtain the aquifer parameters. This paper proposes a novel approach based on a drawdown model and a global optimization method of simulated annealing (SA) or a genetic algorithm (GA) to determine the best-fit aquifer parameters for leaky aquifer systems. The aquifer parameters obtained from SA and the GA almost agree with those obtained from the extended Kalman filter and gradient-type method. Moreover, all results indicate that the SA and GA are robust and yield consistent results when dealing with the parameter identification problems. Copyright © 2006 John Wiley & Sons, Ltd. [source]


    An accelerated algorithm for parameter identification in a hierarchical plasticity model accounting for material constraints

    INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 3 2001
    L. Simoni
    Abstract The parameter identification procedure proposed in this paper is based on the solution of an inverse problem, which relies on the minimization of an error function of least-squares type. The solution of the ensuing optimization problem, which is a constrained one owing to the presence of physical links between the optimization parameters, is performed by means of a particular technique of the feasible direction type, which is modified and improved when the problem turns to an unconstrained one. The algorithm is particularly efficient in the presence of hierarchical material models. The numerical properties of the proposed procedure are discussed and its behaviour is compared with usual optimization methods when applied to constrained and unconstrained problems. Copyright © 2001 John Wiley & Sons, Ltd. [source]


    A structural optimization method based on the level set method using a new geometry-based re-initialization scheme

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 12 2010
    Shintaro Yamasaki
    Abstract Structural optimization methods based on the level set method are a new type of structural optimization method where the outlines of target structures can be implicitly represented using the level set function, and updated by solving the so-called Hamilton,Jacobi equation based on a Eulerian coordinate system. These new methods can allow topological alterations, such as the number of holes, during the optimization process whereas the boundaries of the target structure are clearly defined. However, the re-initialization scheme used when updating the level set function is a critical problem when seeking to obtain appropriately updated outlines of target structures. In this paper, we propose a new structural optimization method based on the level set method using a new geometry-based re-initialization scheme where both the numerical analysis used when solving the equilibrium equations and the updating process of the level set function are performed using the Finite Element Method. The stiffness maximization, eigenfrequency maximization, and eigenfrequency matching problems are considered as optimization problems. Several design examples are presented to confirm the usefulness of the proposed method. Copyright © 2010 John Wiley & Sons, Ltd. [source]


    Topology optimization for stationary fluid,structure interaction problems using a new monolithic formulation

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 5 2010
    Gil Ho Yoon
    Abstract This paper outlines a new procedure for topology optimization in the steady-state fluid,structure interaction (FSI) problem. A review of current topology optimization methods highlights the difficulties in alternating between the two distinct sets of governing equations for fluid and structure dynamics (hereafter, the fluid and structural equations, respectively) and in imposing coupling boundary conditions between the separated fluid and solid domains. To overcome these difficulties, we propose an alternative monolithic procedure employing a unified domain rather than separated domains, which is not computationally efficient. In the proposed analysis procedure, the spatial differential operator of the fluid and structural equations for a deformed configuration is transformed into that for an undeformed configuration with the help of the deformation gradient tensor. For the coupling boundary conditions, the divergence of the pressure and the Darcy damping force are inserted into the solid and fluid equations, respectively. The proposed method is validated in several benchmark analysis problems. Topology optimization in the FSI problem is then made possible by interpolating Young's modulus, the fluid pressure of the modified solid equation, and the inverse permeability from the damping force with respect to the design variables. Copyright © 2009 John Wiley & Sons, Ltd. [source]


    Topology optimization of muffler internal partitions for improving acoustical attenuation performance

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 4 2009
    Jin Woo Lee
    Abstract The internal partition configuration of an expansion chamber muffler affects significantly its acoustical transmission characteristics, but the use of systematic optimization methods to muffler design problems is rare. The main objective of this research is to maximize the transmission loss at target frequencies by optimizing partition layouts inside a muffler chamber by formulating an acoustical topology optimization problem. The selected target frequencies include the deep frequencies of a nominal muffler in order to see the critical effects of partition configurations on the acoustical transmission characteristics. The effects of partition volume constraint ratios are also investigated and physics behind the optimized layouts is investigated. Numerical results show that mufflers with optimized partition layouts outperform nominal mufflers considerably, but the shapes and locations of the optimized partitions should be much different from those of conventional partitions. Copyright © 2009 John Wiley & Sons, Ltd. [source]


    Optimization of structural dynamic behaviour based on effective modal parameters

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 5 2007
    S. Besset
    Abstract Optimization of complex structures often leads to high calculation costs. Indeed, the structure has to be frequently reanalysed in order to update the optimization criteria. We propose an optimization method based on effective modal parameters. These parameters are close to the modal matrices used for the modal analysis of a structure. Thus, once the structure has been analysed, it becomes very easy to calculate optimization criteria. First, we will explain the modal analysis that we will use in this paper. A modal model will be used to analyse the hollow parts of the structure. The modal analysis of the whole structure will be performed using substructuring and ,double modal synthesis' proposed by Jezequel. Secondly, we will explain how to obtain effective modal parameters and their use for optimization. Finally, we will show the efficiency of these parameters through the optimization of a complex structure, using two types of optimization methods. Copyright © 2006 John Wiley & Sons, Ltd. [source]


    A reduced-order simulated annealing approach for four-dimensional variational data assimilation in meteorology and oceanography

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 11 2008
    I. Hoteit
    Abstract Four-dimensional variational data assimilation in meteorology and oceanography suffers from the presence of local minima in the cost function. These local minima arise when the system under study is strongly nonlinear. The number of local minima further dramatically increases with the length of the assimilation period and often renders the solution to the problem intractable. Global optimization methods are therefore needed to resolve this problem. However, the huge computational burden makes the application of these sophisticated techniques unfeasible for large variational data assimilation systems. In this study, a Simulated Annealing (SA) algorithm, complemented with an order-reduction of the control vector, is used to tackle this problem. SA is a very powerful tool of combinatorial minimization in the presence of several local minima at the cost of increasing the execution time. Order-reduction is then used to reduce the dimension of the search space in order to speed up the convergence rate of the SA algorithm. This is achieved through a proper orthogonal decomposition. The new approach was implemented with a realistic eddy-permitting configuration of the Massachusetts Institute of Technology general circulation model (MITgcm) of the tropical Pacific Ocean. Numerical results indicate that the reduced-order SA approach was able to efficiently reduce the cost function with a reasonable number of function evaluations. Copyright © 2008 John Wiley & Sons, Ltd. [source]


    The harmonic adjoint approach to unsteady turbomachinery design

    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 3-4 2002
    M. C. Duta
    Abstract In recent years, there has been rapid progress in aerodynamic optimization methods which use adjoint flow analysis to efficiently calculate the sensitivity of steady-state objective functions to changes in the underlying design variables. This paper shows that the same adjoint approach can be used in turbomachinery applications in which the primary concern is blade vibration due to harmonic flow unsteadiness. The paper introduces the key engineering concepts and discusses the derivation of the adjoint analysis at the algebraic level. The emphasis is on the algorithmic aspects of the analysis, on the iterative solution method and on the role played by the strong solid wall boundary condition, in particular. The novel ideas are exploited to reveal the potential of the approach in the minimization of the unsteady vibration of turbomachinery blades due to incident wakes. Copyright © 2002 John Wiley & Sons, Ltd. [source]


    Recent advances of neural network-based EM-CAD

    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, Issue 5 2010
    Humayun Kabir
    Abstract In this article, we provide an overview of recent advances in computer-aided design techniques using neural networks for electromagnetic (EM) modeling and design applications. Summary of various recent neural network modeling techniques including passive component modeling, design and optimization using the models are discussed. Training data for the models are generated from EM simulations. The trained neural networks become fast and accurate models of EM structures. The models are then incorporated into various optimization methods and commercially available circuit simulators for fast design and optimization. We also provide an overview of recently developed neural network inverse modeling technique. Training a neural network inverse model directly may become difficult due to the nonuniqueness of the input,output relationship in the inverse model. Training data containing multivalued solutions are divided into groups according to derivative information. Multiple inverse submodels are built based on divided data groups and are then combined to form a complete model. Comparison between the conventional EM-based design approach and the inverse design approach has also been discussed. These computer-aided design techniques using neural models provide circuit level simulation speed with EM level accuracy avoiding the high computational cost of EM simulation. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2010. [source]


    Exhaustive approach to the coupling matrix synthesis problem and application to the design of high degree asymmetric filters

    INTERNATIONAL JOURNAL OF RF AND MICROWAVE COMPUTER-AIDED ENGINEERING, Issue 1 2007
    Richard J. Cameron
    Abstract In this paper a new approach to the synthesis of coupling matrices for microwave filters is presented. The new approach represents an advance on existing direct and optimization methods for coupling matrix synthesis, in that it will exhaustively discover all possible coupling matrix solutions for a network if more than one exists. This enables a selection to be made of the set of coupling values, resonator frequency offsets, parasitic coupling tolerance, etc. that will be best suited to the technology it is intended to realize the microwave filter with. To demonstrate the use of the method, the case of the recently introduced "extended box" coupling matrix configuration is taken. The extended box is a new class of filter configuration adapted to the synthesis of asymmetric filtering characteristics of any degree. For this configuration the number of solutions to the coupling matrix synthesis problem appears to be high and offers therefore some flexibility that can be used during the design phase. We illustrate this by carrying out the synthesis process of two asymmetric filters of 8th and 10th degree. In the first example a ranking criterion is defined in anticipation of a dual mode realization and allows the selection of a "best" coupling matrix out of 16 possible ones. For the 10th degree filter a new technique of approximate synthesis is presented, yielding some simplifications of the practical realization of the filter as well as of its computer aided tuning phase. © 2006 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007. [source]


    Robust fault estimation of uncertain systems using an LMI-based approach

    INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 18 2008
    Euripedes G. Nobrega
    Abstract General recent techniques in fault detection and isolation (FDI) are based on H, optimization methods to address the issue of robustness in the presence of disturbances, uncertainties and modeling errors. Recently developed linear matrix inequality (LMI) optimization methods are currently used to design controllers and filters, which present several advantages over the Riccati equation-based design methods. This article presents an LMI formulation to design full-order and reduced-order robust H, FDI filters to estimate the faulty input signals in the presence of uncertainty and model errors. Several cases are examined for nominal and uncertain plants, which consider a weight function for the disturbance and a reference model for the faults. The FDI LMI synthesis conditions are obtained based on the bounded real lemma for the nominal case and on a sufficient extension for the uncertain case. The conditions for the existence of a feasible solution form a convex problem for the full-order filter, which may be solved via recently developed LMI optimization techniques. For the reduced-order FDI filter, the inequalities include a non-convex constraint, and an alternating projections method is presented to address this case. The examples presented in this paper compare the simulated results of a structural model for the nominal and uncertain cases and show that a degree of conservatism exists in the robust fault estimation; however, more reliable solutions are achieved than the nominal design. Copyright © 2008 John Wiley & Sons, Ltd. [source]


    On the equivalence of the Rietveld method and the correlated integrated intensities method in powder diffraction

    JOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 4 2004
    William I. F. David
    The Rietveld method is the most straightforward and statistically correct approach for the refinement of crystal structure parameters from powder diffraction data. The equivalent two-stage approach, involving the refinement of structural parameters based on integrated intensities extracted using the Pawley method, is extremely useful in circumstances such as the global optimization methods of structure determination, where a great many refinements need to be performed very quickly. The equivalence is emphasized in a simple mathematical relationship between the goodness of fits obtained in Rietveld, Pawley and correlated integrated intensities refinements. A rationale is given for determining the estimated standard deviations for structural variables from powder diffraction data. [source]


    Directional asymmetry of long-distance dispersal and colonization could mislead reconstructions of biogeography

    JOURNAL OF BIOGEOGRAPHY, Issue 5 2005
    Lyn G. Cook
    Abstract Aim, Phylogenies are increasingly being used to attempt to answer biogeographical questions. However, a reliance on tree topology alone has emerged without consideration of earth processes or the biology of the organisms in question. Most ancestral-state optimization methods have inherent problems, including failure to take account of asymmetry, such as unequal probabilities of losses and gains, and the lack of use of independent cost estimates. Here we discuss what we perceive as shortcomings in most current tree-based biogeography interpretation methods and show that consideration of processes and their likelihoods can turn the conventional biogeographical interpretation on its head. Location, Southern hemisphere focus but applicable world-wide. Methods, The logic of existing methods is reviewed with respect to their adequacy in modelling processes such as geographical mode of speciation and likelihood of dispersal, including directional bias. Published reconstructions of dispersal of three plant taxa between Australia and New Zealand were re-analysed using standard parsimony and maximum likelihood (ML) methods with rate matrices to model expected asymmetry of dispersal. Results, Few studies to date incorporate asymmetric dispersal rate matrices or question the simplistic assumption of equal costs. Even when they do, cost matrices typically are not derived independently of tree topology. Asymmetrical dispersal between Australia and New Zealand could be reconstructed using parsimony but not with ML. Main conclusions, The inadequacy of current models has important consequences for our interpretation of southern hemisphere biogeography, particularly in relation to dispersal. For example, if repeated directional dispersals and colonization in the direction of prevailing winds have occurred, with intervening periods of speciation, then there is no need to infer dispersals against those winds. Failure to take account of directionality and other biases in reconstruction methods has implications beyond the simple misinterpretation of the biogeography of a taxonomic group, such as calibration of molecular clocks, the dating of vicariance events, and the prioritization of areas for conservation. [source]


    Noise propagation and error estimations in multivariate curve resolution alternating least squares using resampling methods

    JOURNAL OF CHEMOMETRICS, Issue 7-8 2004
    Joaquim Jaumot
    Abstract Different approaches for the calculation of prediction intervals of estimations obtained in multivariate curve resolution using alternating least squares optimization methods are explored and compared. These methods include Monte Carlo simulations, noise addition and jackknife resampling. Obtained results allow a preliminary investigation of noise effects and error propagation on resolved profiles and on parameters estimated from them. The effect of noise on rotational ambiguities frequently found in curve resolution methods is discussed. This preliminary study is shown for the resolution of a three-component equilibrium system with overlapping concentration and spectral profiles. Copyright © 2004 John Wiley & Sons, Ltd. [source]


    A PM3/d specific reaction parameterization for iron atom in the hydrogen abstraction catalyzed by soybean lipoxygenase-1

    JOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 6 2007
    Ismael Tejero
    Abstract This paper reports a specific reaction parameter (SRP) PM3/d model for iron that can reproduce the DFT/MM results of the hydrogen abstraction reaction from the C11 position of linoleic acid by the Soybean lipoxygenase-1 enzyme. A suite of nonlinear optimization methods is outlined for semiempirical parameter development based on integrated evolutionary (genetic) and direction set minimization algorithms. The PM3/d-SRP Fe parameters are derived along three consecutive steps. The final parameterization step includes the effect of the whole enzyme in order to get a better quantum mechanical/molecular mechanical description. © 2007 Wiley Periodicals, Inc. J Comput Chem, 2007 [source]


    NONLINEAR CONSTRAINED OPTIMIZATION of THERMAL PROCESSING II.

    JOURNAL OF FOOD PROCESS ENGINEERING, Issue 3 2003
    FINITE CYLINDRICAL GEOMETRIES, VARIABLE PROCESS TEMPERATURE PROFILES to REDUCE PROCESS TIME, to IMPROVE NUTRIENT RETENTION IN SPHERICAL
    ABSTRACT Conventional methods for thermal processing of foods use constant processing temperature profiles (CPTPs) for a prescribed processing time, which is based on achieving a required microbial lethality to comply with public health standards. This also results in degradation of nutrients and quality factors. the variable process temperature profiles (VPTPs) obtained by using optimization methods can reduce quality losses and/or processing time compared to CPTPs. the objective of this research was to evaluate VPTPs using the Complex Method to reduce the processing time and/or improve quality retention for a specified level of lethality in thermal processing of conduction heated foods. the VPTPs were obtained for volume average retention of thiamine considering different sizes of spheres (small and large) and finite cylinders (small and large), and the thiamine retention and processing time results were compared with a conventional method (processing at 121.1C) for a specified lethality level. the use of VPTPs resulted in a 37 and 10% decrease in processing times in spherical and 40 % and 6 % for finite cylindrical shapes, for the same objective function value and specified lethality compared to the CPTP process. For the same processing time, the improvements in thiamine destruction were 3.7 and 2 % for spheres, and 3.9 and 2.2% for finite cylinders. [source]


    Comparison of real-time methods for maximizing power output in microbial fuel cells

    AICHE JOURNAL, Issue 10 2010
    L. Woodward
    Abstract Microbial fuel cells (MFCs) constitute a novel power generation technology that converts organic waste to electrical energy using microbially catalyzed electrochemical reactions. Since the power output of MFCs changes considerably with varying operating conditions, the online optimization of electrical load (i.e., external resistance) is extremely important for maintaining a stable MFC performance. The application of several real-time optimization methods is presented, such as the perturbation and observation method, the gradient method, and the recently proposed multiunit method, for maximizing power output of MFCs by varying the external resistance. Experiments were carried out in two similar MFCs fed with acetate. Variations in substrate concentration and temperature were introduced to study the performance of each optimization method in the face of disturbances unknown to the algorithms. Experimental results were used to discuss advantages and limitations of each optimization method. © 2010 American Institute of Chemical Engineers AIChE J, 2010 [source]


    Evolutionary combinatorial chemistry, a novel tool for SAR studies on peptide transport across the blood,brain barrier.

    JOURNAL OF PEPTIDE SCIENCE, Issue 12 2005
    Part 2.
    Abstract The use of high-throughput methods in drug discovery allows the generation and testing of a large number of compounds, but at the price of providing redundant information. Evolutionary combinatorial chemistry combines the selection and synthesis of biologically active compounds with artificial intelligence optimization methods, such as genetic algorithms (GA). Drug candidates for the treatment of central nervous system (CNS) disorders must overcome the blood,brain barrier (BBB). This paper reports a new genetic algorithm that searches for the optimal physicochemical properties for peptide transport across the blood,brain barrier. A first generation of peptides has been generated and synthesized. Due to the high content of N -methyl amino acids present in most of these peptides, their syntheses were especially challenging due to over-incorporations, deletions and DKP formations. Distinct fragmentation patterns during peptide cleavage have been identified. The first generation of peptides has been studied by evaluation techniques such as immobilized artificial membrane chromatography (IAMC), a cell-based assay, log Poctanol/water calculations, etc. Finally, a second generation has been proposed. Copyright © 2005 European Peptide Society and John Wiley & Sons, Ltd. [source]


    Development of fully functional proteins with novel glycosylation via enzymatic glycan trimming

    JOURNAL OF PHARMACEUTICAL SCIENCES, Issue 8 2009
    Melinda L. Toumi
    Abstract Recombinant glycoproteins present unique challenges to biopharmaceutical development, especially when efficacy is affected by glycosylation. In these cases, optimizing the protein's glycosylation is necessary, but difficult, since the glycan structures cannot be genetically encoded, and glycosylation in nonhuman cell lines can be very different from human glycosylation profiles. We are exploring a potential solution to this problem by designing enzymatic glycan optimization methods to produce proteins with useful glycan compositions. To demonstrate viability of this new approach to generating glycoprotein-based pharmaceuticals, the N -linked glycans of a model glycoprotein, ribonuclease B (RNase B), were modified using an ,-mannosidase to produce a new glycoprotein with different glycan structures. The secondary structure of the native and modified glycoproteins was retained, as monitored using circular dichroism. An assay was also developed using an RNA substrate to verify that RNase B had indeed retained its function after being subjected to the necessary glycan modification conditions. This is the first study that verifies both activity and secondary structure of a glycoprotein after enzymatic glycan trimming for use in biopharmaceutical development methods. The evidence of preserved structure and function for a modified glycoprotein indicates that extracellular enzymatic modification methods could be implemented in producing designer glycoproteins. © 2008 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 98:2581,2591, 2009 [source]


    Successful Application of Simplex Methods to the Optimization of Textured Superconducting Ceramics

    JOURNAL OF THE AMERICAN CERAMIC SOCIETY, Issue 7 2004
    Eva Natividad
    The fabrication of ceramic materials implies dealing with a great number of processing variables with clear interaction, which prevents straightforward optimization of the processes. In this paper, we report the optimization process applied to improve the properties of LFZ-textured Bi-2212 superconducting thin rods. In this process, based on Simplex optimization methods, four growth and four annealing parameters were taken as control variables to obtain high critical currents and short processing times. As a result, the critical current values increased by a factor of 3 after only 30 trials. [source]


    Diffusion-equation method for crystallographic figure of merits

    ACTA CRYSTALLOGRAPHICA SECTION A, Issue 5 2010
    Anders J. Markvardsen
    Global optimization methods play a significant role in crystallography, particularly in structure solution from powder diffraction data. This paper presents the mathematical foundations for a diffusion-equation-based optimization method. The diffusion equation is best known for describing how heat propagates in matter. However, it has also attracted considerable attention as the basis for global optimization of a multimodal function [Piela et al. (1989). J. Phys. Chem.93, 3339,3346]. The method relies heavily on available analytical solutions for the diffusion equation. Here it is shown that such solutions can be obtained for two important crystallographic figure-of-merit (FOM) functions that fully account for space-group symmetry and allow the diffusion-equation solution to vary depending on whether atomic coordinates are fixed or not. The resulting expression is computationally efficient, taking the same order of floating-point operations to evaluate as the starting FOM function measured in terms of the number of atoms in the asymmetric unit. This opens the possibility of implementing diffusion-equation methods for crystallographic global optimization algorithms such as structure determination from powder diffraction data. [source]


    Planning and Optimization of a Numerical Control Machine in a Multiple Response Case

    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 5 2006
    Rossella Berni
    Abstract This paper focuses on a specific case of experimental planning and optimization in a multiresponse case. Particularly, our attention is dedicated to a numerical control machine and our final goal is to improve this machine's measurement accuracy for a general dental implant. This work substantially aims at addressing two issues: the optimization methods in the presence of more response variables and the related problem of weighting according to the actual importance of these variables. About simultaneous optimization, we suggest an improvement by a new function which takes care of location and dispersion effects. Copyright © 2006 John Wiley & Sons, Ltd. [source]


    A Genetic Algorithm Hybrid for Constructing Optimal Response Surface Designs

    QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 7 2004
    David Drain
    Abstract Hybrid heuristic optimization methods can discover efficient experiment designs in situations where traditional designs cannot be applied, exchange methods are ineffective, and simple heuristics like simulated annealing fail to find good solutions. One such heuristic hybrid is GASA (genetic algorithm,simulated annealing), developed to take advantage of the exploratory power of the genetic algorithm, while utilizing the local optimum exploitive properties of simulated annealing. The successful application of this method is demonstrated in a difficult design problem with multiple optimization criteria in an irregularly shaped design region. Copyright © 2004 John Wiley & Sons, Ltd. [source]


    Magnetic impurities in small metal clusters

    ANNALEN DER PHYSIK, Issue 9-10 2005
    G.M. Pastor
    Abstract Magnetic impurities in small metallic clusters are investigated in the framework of the Anderson model by using exact diagonalization and geometry optimization methods. The singlet-triplet spin gap ,E shows a remarkable dependence as a function of band-filling, cluster structure, and impurity position that can be interpreted in terms of the environment-specific conduction-electron spectrum. The low-energy spin excitations involve similar energies as isomerizations. Interesting correlations between cluster structure and magnetic behavior are revealed. Finite-temperature properties such as specific heat, effective impurity moment, and magnetic susceptibility are calculated exactly in the canonical ensemble. A finite-size equivalent of the Kondo effect is identified and its structural dependence is discussed. [source]