Home About us Contact
|
Home About us Contact | ||
|
|
||
Sequential Quadratic Programming (sequential + quadratic_programming)
Selected AbstractsSequential 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] 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] 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] 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] 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] 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] | |||||||||||||