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Quadratic Programming (quadratic + programming)
Kinds of Quadratic Programming Selected AbstractsA practical approach for estimating illumination distribution from shadows using a single imageINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 2 2005Taeone Kim Abstract This article presents a practical method that estimates illumination distribution from shadows using only a single image. The shadows are assumed to be cast on a textured, Lambertian surface by an object of known shape. Previous methods for illumination estimation from shadows usually require that the reflectance property of the surface on which shadows are cast be constant or uniform, or need an additional image to cancel out the effects of varying albedo of the textured surface on illumination estimation. But, our method deals with an estimation problem for which surface albedo information is not available. In this case, the estimation problem corresponds to an underdetermined one. We show that the combination of regularization by correlation and some user-specified information can be a practical method for solving the underdetermined problem. In addition, as an optimization tool for solving the problem, we develop a constrained Non-Negative Quadratic Programming (NNQP) technique into which not only regularization but also multiple linear constraints induced by user-specified information are easily incorporated. We test and validate our method on both synthetic and real images and present some experimental results. © 2005 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 15, 143,154, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20047 [source] Sequential Quadratic Programming for Development of a New Probiotic Dairy Tofu with Glucono-,-LactoneJOURNAL OF FOOD SCIENCE, Issue 7 2004M.-J. Chen ABSTRACT: The purpose of this research was to evaluate the effects of various concentrations of glucono-,-lactone (GDL) and skim milk powder, as well as the addition of prebiotics, on the rheology and probiotic viabilities of dairy tofu. Additionally, modern optimization techniques were applied to attempt to determine the optimal processing conditions and growth rate for the selected probiotics (Lactobacillus. acidophilus, L. casei, Bifidobacteria bifidum, and B. longum). There were 2 stages in this research to accomplish the goal. The 1st stage was to derive surface models using response surface methodology (RSM); the 2nd stage performed optimization on the models using sequential quadratic programming (SQP) techniques. The results were demonstrated to be effective. The most favorable production conditions of dairy tofu were 1% GDL, 0% peptides, 3% isomaltooligosaccharides (IMO), and 18% milk, as confirmed by subsequent verification experiments. Analysis of the sensory evaluation results revealed no significant difference between the probiotic dairy tofu and the GDL analog in terms of texture and appearance (P < 0.05). The viable numbers of probiotics were well above the recommended limit of 106 CFU/g for the probiotic dairy tofu throughout the tested storage period. [source] Food consumption impacts of adherence to dietary norms in the United States: a quantitative assessmentAGRICULTURAL ECONOMICS, Issue 2-3 2007C. S. Srinivasan Dietary norms; Dietary adjustment; Food consumption impacts; Quadratic programming Abstract Promotion of adherence to healthy-eating norms has become an important element of nutrition policy in the United States and other developed countries. We assess the potential consumption impacts of adherence to a set of recommended dietary norms in the United States using a mathematical programming approach. We find that adherence to recommended dietary norms would involve significant changes in diets, with large reductions in the consumption of fats and oils along with large increases in the consumption of fruits, vegetables, and cereals. Compliance with norms recommended by the World Health Organization for energy derived from sugar would involve sharp reductions in sugar intakes. We also analyze how dietary adjustments required vary across demographic groups. Most socio-demographic characteristics appear to have relatively little influence on the pattern of adjustment required to comply with norms. Income levels have little effect on required dietary adjustments. Education is the only characteristic to have a significant influence on the magnitude of adjustments required. The least educated rather than the poorest have to bear the highest burden of adjustment. Our analysis suggests that fiscal measures like nutrient-based taxes may not be as regressive as commonly believed. Dissemination of healthy-eating norms to the less educated will be a key challenge for nutrition policy. [source] Dynamic Metabolic Modeling for a MAB BioprocessBIOTECHNOLOGY PROGRESS, Issue 1 2007Jianying Gao Production of monoclonal antibodies (MAb) for diagnostic or therapeutic applications has become an important task in the pharmaceutical industry. The efficiency of high-density reactor systems can be potentially increased by model-based design and control strategies. Therefore, a reliable kinetic model for cell metabolism is required. A systematic procedure based on metabolic modeling is used to model nutrient uptake and key product formation in a MAb bioprocess during both the growth and post-growth phases. The approach combines the key advantages of stoichiometric and kinetic models into a complete metabolic network while integrating the regulation and control of cellular activity. This modeling procedure can be easily applied to any cell line during both the cell growth and post-growth phases. Quadratic programming (QP) has been identified as a suitable method to solve the underdetermined constrained problem related to model parameter identification. The approach is illustrated for the case of murine hybridoma cells cultivated in stirred spinners. [source] Adding Depth to Cartoons Using Sparse Depth (In)equalitiesCOMPUTER GRAPHICS FORUM, Issue 2 2010D. Sıkora Abstract This paper presents a novel interactive approach for adding depth information into hand-drawn cartoon images and animations. In comparison to previous depth assignment techniques our solution requires minimal user effort and enables creation of consistent pop-ups in a matter of seconds. Inspired by perceptual studies we formulate a custom tailored optimization framework that tries to mimic the way that a human reconstructs depth information from a single image. Its key advantage is that it completely avoids inputs requiring knowledge of absolute depth and instead uses a set of sparse depth (in)equalities that are much easier to specify. Since these constraints lead to a solution based on quadratic programming that is time consuming to evaluate we propose a simple approximative algorithm yielding similar results with much lower computational overhead. We demonstrate its usefulness in the context of a cartoon animation production pipeline including applications such as enhancement, registration, composition, 3D modelling and stereoscopic display. [source] Optimization of Train Speed Profile for Minimum Energy ConsumptionIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 3 2010Masafumi Miyatake Member Abstract The optimal operation of railway systems minimizing total energy consumption is discussed in this paper. Firstly, some measures of finding energy-saving train speed profiles are outlined. After the characteristics that should be considered in optimizing train operation are clarified, complete optimization based on optimal control theory is reviewed. Their basic formulations are summarized taking into account most of the difficult characteristics peculiar to railway systems. Three methods of solving the formulation, dynamic programming (DP), gradient method, and sequential quadratic programming (SQP), are introduced. The last two methods can also control the state of charge (SOC) of the energy storage devices. By showing some numerical results of simulations, the significance of solving not only optimal speed profiles but also optimal SOC profiles of energy storage are emphasized, because the numerical results are beyond the conventional qualitative studies. Future scope for applying the methods to real-time optimal control is also mentioned. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source] Energy Saving Speed and Charge/Discharge Control of a Railway Vehicle with On-board Energy Storage by Means of an Optimization ModelIEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, Issue 6 2009Masafumi Miyatake Member Abstract The optimal operation of rail vehicle minimizing total energy consumption is discussed in this paper. In recent years, the energy storage devices have enough energy and power density to use in trains as on-board energy storage. The on-board storage can assist the acceleration/deceleration of the train and may decrease energy consumption. Many works on the application of the energy storage devices to trains were reported, however, they did not deal enough with the optimality of the control of the devices. The authors pointed out that the charging/discharging command and vehicle speed profile should be optimized together based on the optimality analysis. The authors have developed the mathematical model based on a general optimization technique, sequential quadratic programming. The proposed method can determine the optimal acceleration/deceleration and current commands at every sampling point under fixed conditions of transfer time and distance. Using the proposed method, simulations were implemented in some cases. The electric double layer capacitor (EDLC) is assumed as an energy storage device in our study, because of its high power density etc. The trend of optimal solutions such as values of control inputs and energy consumption is finally discussed. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [source] The use of an SQP algorithm in slope stability analysisINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 1 2005Jian Chen Abstract In the upper bound approach to limit analysis of slope stability based on the rigid finite element method, the search for the minimum factor of safety can be formulated as a non-linear programming problem with equality constraints only based on a yield criterion, a flow rule, boundary conditions, and an energy-work balance equation. Because of the non-linear property of the resulting optimization problems, a non-linear mathematical programming algorithm has to be employed. In this paper, the relations between the numbers of nodes, elements, interfaces, and subsequent unknowns and constraints in the approach have been derived. It can be shown that in the large-scale problems, the unknowns are subject to a highly sparse set of equality constraints. Because of the existence of non-linear equalities in the approach, this paper applies first time a special sequential quadratic programming (SQP) algorithm, feasible SQP (FSQP), to obtain solutions for such non-linear optimization problems. In FSQP algorithm, the non-linear equality constraints are turned into inequality constraints and the objective function is replaced by an exact penalty function which penalizes non-linear equality constraint violations only. Three numerical examples are presented to illustrate the potentialities and efficiencies of the FSQP algorithm in the slope stability analysis. Copyright © 2004 John Wiley & Sons, Ltd. [source] Elasto-plasticity revisited: numerical analysis via reproducing kernel particle method and parametric quadratic programmingINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING, Issue 6 2002K. M. Liew Abstract Aiming to simplify the solution process of elasto-plastic problems, this paper proposes a reproducing kernel particle algorithm based on principles of parametric quadratic programming for elasto-plasticity. The parametric quadratic programming theory is useful and effective for the assessment of certain features of structural elasto-plastic behaviour and can also be exploited for numerical iteration. Examples are presented to illustrate the essential aspects of the behaviour of the model proposed and the flexibility of the coupled parametric quadratic programming formulations with the reproducing kernel particle method. Copyright © 2002 John Wiley & Sons, Ltd. [source] CFD-based optimization of aerofoils using radial basis functions for domain element parameterization and mesh deformationINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 8 2008A. M. Morris Abstract A novel domain element shape parameterization method is presented for computational fluid dynamics-based shape optimization. The method is to achieve two aims: (1) provide a generic ,wrap-around' optimization tool that is independent of both flow solver and grid generation package and (2) provide a method that allows high-fidelity aerodynamic optimization of two- and three-dimensional bodies with a low number of design variables. The parameterization technique uses radial basis functions to transfer domain element movements into deformations of the design surface and corresponding aerodynamic mesh, thus allowing total independence from the grid generation package (structured or unstructured). Independence from the flow solver (either inviscid, viscous, aeroelastic) is achieved by obtaining sensitivity information for an advanced gradient-based optimizer (feasible sequential quadratic programming) by finite-differences. Results are presented for two-dimensional aerofoil inverse design and drag optimization problems. Inverse design results demonstrate that a large proportion of the design space is feasible with a relatively low number of design variables using the domain element parameterization. Heavily constrained (in lift, volume, and moment) two-dimensional aerofoil drag optimization has shown that significant improvements over existing designs can be achieved using this method, through the use of various objective functions. Copyright © 2008 John Wiley & Sons, Ltd. [source] CFD-based multi-objective optimization method for ship designINTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, Issue 5 2006Yusuke Tahara Abstract This paper concerns development and demonstration of a computational fluid dynamics (CFD)-based multi-objective optimization method for ship design. Three main components of the method, i.e. computer-aided design (CAD), CFD, and optimizer modules are functionally independent and replaceable. The CAD used in the present study is NAPA system, which is one of the leading CAD systems in ship design. The CFD method is FLOWPACK version 2004d, a Reynolds-averaged Navier,Stokes (RaNS) solver developed by the present authors. The CFD method is implemented into a self-propulsion simulator, where the RaNS solver is coupled with a propeller-performance program. In addition, a maneuvering simulation model is developed and applied to predict ship maneuverability performance. Two nonlinear optimization algorithms are used in the present study, i.e. the successive quadratic programming and the multi-objective genetic algorithm, while the former is mainly used to verify the results from the latter. For demonstration of the present method, a multi-objective optimization problem is formulated where ship propulsion and maneuverability performances are considered. That is, the aim is to simultaneously minimize opposite hydrodynamic performances in design tradeoff. In the following, an overview of the present method is given, and results are presented and discussed for tanker stern optimization problem including detailed verification work on the present numerical schemes. Copyright © 2006 John Wiley & Sons, Ltd. [source] Constrained closed-loop control of depth of anaesthesia in the operating theatre during surgeryINTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 5 2005M. Mahfouf Abstract The constrained version of generalized predictive control (GPC) which employs the quadratic programming (QP) approach is evaluated for on-line administration of an anaesthetic drug in the operating theatre during surgery. In the first instance, a patient simulator was developed using a physiological model of the patient and the necessary control software was validated via a series of extensive simulation experiments. Such a validated system was then transferred into the operating theatre for a series of clinical evaluation trials. The clinical trials, which were performed with little involvement of the design engineer, led to a good regulation of unconsciousness using fixed-parameters as well the adaptive version of the algorithm. Furthermore, the constrained algorithm displayed good robustness properties against disturbances such as high stimulus levels and allowed for safe and economically effective administration of the anaesthetic agent isoflurane. Copyright © 2005 John Wiley & Sons, Ltd. [source] Prediction model for increasing propylene from FCC gasoline secondary reactions based on Levenberg,Marquardt algorithm coupled with support vector machinesJOURNAL OF CHEMOMETRICS, Issue 9 2010Xiaowei Zhou Abstract Levenberg,Marquardt (LM) algorithm was adopted to optimize the multiple parameters of the support vector machines (SVM) model to overcome the difficulty in selecting the parameters of SVM and to fit relational expression of high nonlinearity. Strategy of dividing the training data into working data to train SVM and the testing data so as to avoid over-fitting was performed. Comparison of the proposed LM/SVM method with three reported hybridized SVM approaches (GA/SVM, SM/SVM and SQP/SVM) was also carried out. The new method was applied in modelling for the prediction of propylene by secondary reactions of FCC gasoline. Best performance of LM/SVM employing polynomial kernel was demonstrated. Good agreement between predicted results and experimental data suggests that the LM/SVM method is successfully developed and the SVM model for increasing propylene is well established. Finally, sequential quadratic programming (SQP) algorithm was employed to optimize the operation conditions of FCC gasoline secondary reaction for maximizing the propylene yield. The obtained optimization conditions are consistent with experimental data and reported results, indicating that the optimization results are reliable. Copyright © 2010 John Wiley & Sons, Ltd. [source] Sequential Quadratic Programming for Development of a New Probiotic Dairy Tofu with Glucono-,-LactoneJOURNAL OF FOOD SCIENCE, Issue 7 2004M.-J. Chen ABSTRACT: The purpose of this research was to evaluate the effects of various concentrations of glucono-,-lactone (GDL) and skim milk powder, as well as the addition of prebiotics, on the rheology and probiotic viabilities of dairy tofu. Additionally, modern optimization techniques were applied to attempt to determine the optimal processing conditions and growth rate for the selected probiotics (Lactobacillus. acidophilus, L. casei, Bifidobacteria bifidum, and B. longum). There were 2 stages in this research to accomplish the goal. The 1st stage was to derive surface models using response surface methodology (RSM); the 2nd stage performed optimization on the models using sequential quadratic programming (SQP) techniques. The results were demonstrated to be effective. The most favorable production conditions of dairy tofu were 1% GDL, 0% peptides, 3% isomaltooligosaccharides (IMO), and 18% milk, as confirmed by subsequent verification experiments. Analysis of the sensory evaluation results revealed no significant difference between the probiotic dairy tofu and the GDL analog in terms of texture and appearance (P < 0.05). The viable numbers of probiotics were well above the recommended limit of 106 CFU/g for the probiotic dairy tofu throughout the tested storage period. [source] A priori information in a regularized sinogram-based method for removing ring artefacts in tomographyJOURNAL OF SYNCHROTRON RADIATION, Issue 4 2010Sofya Titarenko Ring artefacts in X-ray computerized tomography reconstructions are considered. The authors propose a ring artefact removal method based on a priori information regarding the sinogram including smoothness along the horizontal coordinate, symmetry of the first and the final rows and consideration of small perturbations during acquisition. The method does not require prior reconstruction of the original or corrected sinograms. Its numerical implementation is based on quadratic programming. Its efficacy is examined with regard to experimental data sets collected on graphite and bone. [source] Bi-criteria optimal control of redundant robot manipulators using LVI-based primal-dual neural networkOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 3 2010Binghuang Cai Abstract In this paper, a bi-criteria weighting scheme is proposed for the optimal motion control of redundant robot manipulators. To diminish the discontinuity phenomenon of pure infinity-norm velocity minimization (INVM) scheme, the proposed bi-criteria redundancy-resolution scheme combines the minimum kinetic energy scheme and the INVM scheme via a weighting factor. Joint physical limits such as joint limits and joint-velocity limits could also be incorporated simultaneously into the scheme formulation. The optimal kinematic control scheme can be reformulated finally as a quadratic programming (QP) problem. As the real-time QP solver, a primal-dual neural network (PDNN) based on linear variational inequalities (LVI) is developed as well with a simple piecewise-linear structure and global exponential convergence to optimal solutions. Since the LVI-based PDNN is matrix-inversion free, it has higher computational efficiency in comparison with dual neural networks. Computer simulations performed based on the PUMA560 manipulator illustrate the validity and advantages of such a bi-criteria neural optimal motion-control scheme for redundant robots. Copyright © 2009 John Wiley & Sons, Ltd. [source] Direct optimization of dynamic systems described by differential-algebraic equationsOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 6 2008Brian C. Fabien Abstract This paper presents a method for the optimization of dynamic systems described by index-1 differential-algebraic equations (DAE). The class of problems addressed include optimal control problems and parameter identification problems. Here, the controls are parameterized using piecewise constant inputs on a grid in the time interval of interest. In addition, the DAE are approximated using a Rosenbrock,Wanner (ROW) method. In this way the infinite-dimensional optimal control problem is transformed into a finite-dimensional nonlinear programming problem (NLP). The NLP is solved using a sequential quadratic programming (QP) technique that minimizes the L, exact penalty function, using only strictly convex QP subproblems. This paper shows that the ROW method discretization of the DAE leads to (i) a relatively small NLP problem and (ii) an efficient technique for evaluating the function, constraints and gradients associated with the NLP problem. This paper also investigates a state mesh refinement technique that ensures a sufficiently accurate representation of the optimal state trajectory. Two nontrivial examples are used to illustrate the effectiveness of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd. [source] Optimal control of a revenue management system with dynamic pricing facing linear demandOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 6 2006Fee-Seng Chou Abstract This paper considers a dynamic pricing problem over a finite horizon where demand for a product is a time-varying linear function of price. It is assumed that at the start of the horizon there is a fixed amount of the product available. The decision problem is to determine the optimal price at each time period in order to maximize the total revenue generated from the sale of the product. In order to obtain structural results we formulate the decision problem as an optimal control problem and solve it using Pontryagin's principle. For those problems which are not easily solvable when formulated as an optimal control problem, we present a simple convergent algorithm based on Pontryagin's principle that involves solving a sequence of very small quadratic programming (QP) problems. We also consider the case where the initial inventory of the product is a decision variable. We then analyse the two-product version of the problem where the linear demand functions are defined in the sense of Bertrand and we again solve the problem using Pontryagin's principle. A special case of the optimal control problem is solved by transforming it into a linear complementarity problem. For the two-product problem we again present a simple algorithm that involves solving a sequence of small QP problems and also consider the case where the initial inventory levels are decision variables. Copyright © 2006 John Wiley & Sons, Ltd. [source] Trajectory optimization involving sloshing mediaOPTIMAL CONTROL APPLICATIONS AND METHODS, Issue 1 2002Harald Leonpacher Abstract This paper is concerned with the optimization of the transport motion of an open topped fluid filled container within a warehouse environment. In particular, optimal trajectories of the motion of the driver,container system in two-dimensional space will be investigated via numerical solutions of the model equations using sequential quadratic programming. The fluid and the mechanical facility that moves the container are subject to several constraints. The objective of the optimization is the time to transport the container from an initial position to its final destination within the warehouse. Optimization criteria are investigated to control the movement of the fluid within the container. The systems of ordinary and partial differential equations, representing the dynamics of the models are solved numerically using a direct shooting method. The resulting non-linear programming problem is solved using sequential quadratic programming (SQP). Copyright © 2002 John Wiley & Sons, Ltd. [source] | |||||||||||||||||||||||||