Optimization of multiclass queueing networks with changeover times via the achievable region approach: Part I, the single-station case

We address the performance optimization problem in a single-stationmulticlass queueing network with changeover times by means of theachievable region approach. This approach seeks to obtainperformance bounds and scheduling policies from the solution of amathematical program over a relaxation of the system's performanceregion. Relaxed formulations (including linear, convex, nonconvexand positive semidefinite constraints) of this region are developedby formulating equilibrium relations satisfied by the system, withthe help of Palm calculus. Our contributions include: (1) newconstraints formulating equilibrium relations on server dynamics;(2) a flow conservation interpretation of the constraintspreviously derived by the potential function method; (3) newpositive semidefinite constraints; (4) new work decomposition lawsfor single-station multiclass queueing networks, which yield newconvex constraints; (5) a unified buffer occupancy method ofperformance analysis obtained from the constraints; (6) heuristicscheduling policies from the solution of the relaxations.

Optimization of multiclass queueing networks with changeover times via the achievable region method: Part II, the multi-station case

We address the problem of scheduling a multi-station multiclassqueueing network (MQNET) with server changeover times to minimizesteady-state mean job holding costs. We present new lower boundson the best achievable cost that emerge as the values ofmathematical programming problems (linear, semidefinite, andconvex) over relaxed formulations of the system's achievableperformance region. The constraints on achievable performancedefining these formulations are obtained by formulatingsystem's equilibrium relations. Our contributions include: (1) aflow conservation interpretation and closed formulae for theconstraints previously derived by the potential function method;(2) new work decomposition laws for MQNETs; (3) new constraints(linear, convex, and semidefinite) on the performance region offirst and second moments of queue lengths for MQNETs; (4) a fastbound for a MQNET with N customer classes computed in N steps; (5)two heuristic scheduling policies: a priority-index policy, anda policy extracted from the solution of a linear programmingrelaxation.

Generalized Multiobjective Multitree model solution using MOEA

In a previous paper a novel Generalized Multiobjective Multitree model (GMM-model) was proposed. This model considers for the first time multitree-multicast load balancing with splitting in a multiobjective context, whose mathematical solution is a whole Pareto optimal set that can include several results than it has been possible to find in the publications surveyed. To solve the GMM-model, in this paper a multi-objective evolutionary algorithm (MOEA) inspired by the Strength Pareto Evolutionary Algorithm (SPEA) is proposed. Experimental results considering up to 11 different objectives are presented for the well-known NSF network, with two simultaneous data flows

Improvement of the quality factor of RF integrated inductors by layout optimization

A systematic method to improve the quality (Q) factor of RF integrated inductors is presented in this paper. The proposed method is based on the layout optimization to minimize the series resistance of the inductor coil, taking into account both ohmic losses, due to conduction currents, and magnetically induced losses, due to eddy currents. The technique is particularly useful when applied to inductors in which the fabrication process includes integration substrate removal. However, it is also applicable to inductors on low-loss substrates. The method optimizes the width of the metal strip for each turn of the inductor coil, leading to a variable strip-width layout. The optimization procedure has been successfully applied to the design of square spiral inductors in a silicon-based multichip-module technology, complemented with silicon micromachining postprocessing. The obtained experimental results corroborate the validity of the proposed method. A Q factor of about 17 have been obtained for a 35-nH inductor at 1.5 GHz, with Q values higher than 40 predicted for a 20-nH inductor working at 3.5 GHz. The latter is up to a 60% better than the best results for a single strip-width inductor working at the same frequency.

Use of information on the manufacture of samples for the optical characterization of multilayers through a global optimization

We present a procedure for the optical characterization of thin-film stacks from spectrophotometric data. The procedure overcomes the intrinsic limitations arising in the numerical determination of manyparameters from reflectance or transmittance spectra measurements. The key point is to use all theinformation available from the manufacturing process in a single global optimization process. The method is illustrated by a case study of solgel applications.

Computer-aided procedure for optimization of layer thickness uniformity in thermal evaporation physical vapor deposition chambers for lens coating

A computer-aided method to improve the thickness uniformity attainable when coating multiple substrates inside a thermal evaporation physical vapor deposition unit is presented. The study is developed for the classical spherical (dome-shaped) calotte and also for a plane sector reversible holder setup. This second arrangement is very useful for coating both sides of the substrate, such as antireflection multilayers on lenses. The design of static correcting shutters for both kinds of configurations is also discussed. Some results of using the method are presented as an illustration.

Optimization of laser interferometers for the detection of gravitational waves from coalescing binaries

Coalescing compact binary systems are important sources of gravitational waves. Here we investigate the detectability of this gravitational radiation by the recently proposed laser interferometers. The spectral density of noise for various practicable configurations of the detector is also reviewed. This includes laser interferometers with delay lines and Fabry-Prot cavities in the arms, both in standard and dual recycling arrangements. The sensitivity of the detector in all those configurations is presented graphically and the signal-to-noise ratio is calculated numerically. For all configurations we find values of the detector's parameters which maximize the detectability of coalescing binaries, the discussion comprising Newtonian- as well as post-Newtonian-order effects. Contour plots of the signal-to-noise ratio are also presented in certain parameter domains which illustrate the interferometer's response to coalescing binary signals.

Optimization of analytical methods for the assessment of the quality of fats and oils used in continuous deep fat frying

La aplicabilidad, repetibilidad y capacidad de diferentes métodos de análisis para discriminar muestras de aceites con diferentes grados de oxidación fueron evaluadas mediante aceites recogidos en procesos de fritura en continuo en varias empresas españolas. El objetivo de este trabajo fue encontrar métodos complementarios a la determinación del índice de acidez para el control de calidad rutinario de los aceites de fritura empleados en estas empresas. La optimización de la determinación de la constante dieléctrica conllevó una clara mejora de la variabilidad. No obstante, excepto en el caso del índice del ATB, el resto de métodos ensayados mostraron una menor variabilidad. La determinación del índice del ATB fue descartada ya que su sensibilidad fue insuficiente para discriminar entre aceites con diferente grado de oxidación. Los diferentes parámetros de alteración determinados en los aceites de fritura mostraron correlaciones significativas entre el índice de acidez y varios parámetros de oxidación diferentes, como la constante dieléctrica, el índice de p-anisidina, la absorción al ultravioleta y el contenido en polímeros de los triacilgliceroles. El índice de acidez solo evalúa la alteración hidrolítica, por lo que estos parámetros aportan información complementaria al evaluar la alteración termooxidativa.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

Optimization of KOH etching process to obtain textured substrates suitable for heterojunction solar cells fabricated by HWCVD

In this work, we have studied the texturization process of (100) c-Si wafers using a low concentration potassium hydroxide solution in order to obtain good quality textured wafers. The optimization of the etching conditions have led to random but uniform pyramidal structures with good optical properties. Then, symmetric heterojunctions were deposited by Hot-Wire CVD onto these substrates and the Quasi-Steady-State PhotoConductance technique was used to measure passivation quality. Little degradation in the effective lifetime and implicit open circuit voltage of these devices (< 20 mV) was observed in all cases. It is especially remarkable that for big uniform pyramids, the open-circuit voltage is comparable to the values obtained on flat substrates.

Design and optimization of selfnanoemulsifying drug delivery systems for enhanced dissolution of gemfibrozil

Self-nanoemulsifying drug delivery systems of gemfibrozil were developed under Quality by Design approach for improvement of dissolution and oral absorption. Preliminary screening was performed to select proper components combination. BoxBehnken experimental design was employed as statistical tool to optimize the formulation variables, X1 (Cremophor® EL), X2 (Capmul® MCM-C8), and X3 (lemon essential oil). Systems were assessed for visual characteristics (emulsification efficacy), turbidity, droplet size, polydispersity index and drug release. Different pH media were also assayed for optimization. Following optimization, the values of formulation components (X1, X2, and X3) were 32.43%, 29.73% and 21.62%, respectively (16.22% of gemfibrozil). Transmission electron microscopy demonstrated spherical droplet morphology. SNEEDS release study was compared to commercial tablets. Optimized SNEDDS formulation of gemfibrozil showed a significant increase in dissolution rate compared to conventional tablets. Both formulations followed Weibull mathematical model release with a significant difference in td parameter in favor of the SNEDDS. Equally amodelistic parameters were calculated being the dissolution efficiency significantly higher for SNEDDS, confirming that the developed SNEDDS formulation was superior to commercial formulation with respect to in vitro dissolution profile. This paper provides an overview of the SNEDDS of the gemfibrozil as a promising alternative to improve oral absorption.

Some optimization and decision problems in proportional reinsurance

Reinsurance is one of the tools that an insurer can use to mitigate the underwriting risk and then to control its solvency. In this paper, we focus on the proportional reinsurance arrangements and we examine several optimization and decision problems of the insurer with respect to the reinsurance strategy. To this end, we use as decision tools not only the probability of ruin but also the random variable deficit at ruin if ruin occurs. The discounted penalty function (Gerber & Shiu, 1998) is employed to calculate as particular cases the probability of ruin and the moments and the distribution function of the deficit at ruin if ruin occurs.

Orthologous and heterologous expression of a protein from Saccharomyces cerevisiae: Optimization for a biotechnological application

In this thesis (TFG) the results of the comparison between different methods to obtain a recombinant protein, by orthologous and heterologous expression, are exposed. This study will help us to identify the best way to express and purify a recombinant protein that will be used for biotechnology applications. In the first part of the project the goal was to find the best expression and purification system to obtain the recombinant protein of interest. To achieve this objective, a system expression in bacteria and in yeast was designed. The DNA was cloned into two different expression vectors to create a fusion protein with two different tags, and the expression of the protein was induced by IPTG or glucose. Additionally, in yeast, two promoters where used to express the protein, the one corresponding to the same protein (orthologous expression), and the ENO2 promoter (heterologous expression). The protein of interest is a NAD-dependent enzyme so, in a second time, its specific activity was evaluated by coenzyme conversion. The results of the TFG suggest that, comparing the model organisms, bacteria are more efficient than yeast because the quantity of protein obtained is higher and better purified. Regarding yeast, comparing the two expression mechanisms that were designed, heterologous expression works much better than the orthologous expression, so in case that we want to use yeast as expression model for the protein of interest, ENO2 will be the best option. Finally, the enzymatic assays, done to compare the effectiveness of the different expression mechanisms respect to the protein activity, revealed that the protein purified in yeast had more activity in converting the NAD coenzyme.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications