951 resultados para Mixed-integer linear programming


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This study aimed to evaluate the relationship between the cost and energy density of diet consumed in Brazilian households. Data from the Brazilian Household Budget Survey (POF 200812009) were used to identify the main foods and their prices. Similar items were grouped, resulting in a basket of 67 products. Linear programming was applied for the composition of isoenergetic baskets, minimizing the deviation from the average household diet. Restrictions were imposed on the inclusion of items and the energy contribution of the various food groups. A reduction in average cost of diet was applied at intervals of R$0.15 to the lowest possible cost. We identified an inverse association between energy density and cost of diet (p < 0.05), and at the lowest possible cost we obtained the maximum value of energy density Restrictions on the diet's cost resulted in the selection of diets with higher energy density, indicating that cost of diet may lead to the adoption of inadequate diets in Brazil.

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The aim of solving the Optimal Power Flow problem is to determine the optimal state of an electric power transmission system, that is, the voltage magnitude and phase angles and the tap ratios of the transformers that optimize the performance of a given system, while satisfying its physical and operating constraints. The Optimal Power Flow problem is modeled as a large-scale mixed-discrete nonlinear programming problem. This paper proposes a method for handling the discrete variables of the Optimal Power Flow problem. A penalty function is presented. Due to the inclusion of the penalty function into the objective function, a sequence of nonlinear programming problems with only continuous variables is obtained and the solutions of these problems converge to a solution of the mixed problem. The obtained nonlinear programming problems are solved by a Primal-Dual Logarithmic-Barrier Method. Numerical tests using the IEEE 14, 30, 118 and 300-Bus test systems indicate that the method is efficient. (C) 2012 Elsevier B.V. All rights reserved.

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Electrothermomechanical MEMS are essentially microactuators that operate based on the thermoelastic effect induced by the Joule heating of the structure. They can be easily fabricated and require relatively low excitation voltages. However, the actuation time of an electrothermomechanical microdevice is higher than the actuation times related to electrostatic and piezoelectric actuation principles. Thus, in this research, we propose an optimization framework based on the topology optimization method applied to transient problems, to design electrothermomechanical microactuators for response time reduction. The objective is to maximize the integral of the output displacement of the actuator, which is a function of time. The finite element equations that govern the time response of the actuators are provided. Furthermore, the Solid Isotropic Material with Penalization model and Sequential Linear Programming are employed. Finally, a smoothing filter is implemented to control the solution. Results aiming at two distinct applications suggest the proposed approach can provide more than 50% faster actuators. (C) 2012 Elsevier B.V. All rights reserved.

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Abstract This paper describes a design methodology for piezoelectric energy harvester s that thinly encapsulate the mechanical devices and expl oit resonances from higher- order vibrational modes. The direction of polarization determines the sign of the pi ezoelectric tensor to avoid cancellations of electric fields from opposite polarizations in the same circuit. The resultant modified equations of state are solved by finite element method (FEM). Com- bining this method with the solid isotropic material with penalization (SIMP) method for piezoelectric material, we have developed an optimization methodology that optimizes the piezoelectric material layout and polarization direc- tion. Updating the density function of the SIMP method is performed based on sensitivity analysis, the sequen- tial linear programming on the early stage of the opti- mization, and the phase field method on the latter stage

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Small scale fluid flow systems have been studied for various applications, such as chemical reagent dosages and cooling devices of compact electronic components. This work proposes to present the complete cycle development of an optimized heat sink designed by using Topology Optimization Method (TOM) for best performance, including minimization of pressure drop in fluid flow and maximization of heat dissipation effects, aiming small scale applications. The TOM is applied to a domain, to obtain an optimized channel topology, according to a given multi-objective function that combines pressure drop minimization and heat transfer maximization. Stokes flow hypothesis is adopted. Moreover, both conduction and forced convection effects are included in the steady-state heat transfer model. The topology optimization procedure combines the Finite Element Method (to carry out the physical analysis) with Sequential Linear Programming (as the optimization algorithm). Two-dimensional topology optimization results of channel layouts obtained for a heat sink design are presented as example to illustrate the design methodology. 3D computational simulations and prototype manufacturing have been carried out to validate the proposed design methodology.

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Colloidal nanoparticles are additives to improve or modify several properties of thermoplastic or elastic polymers. Usually colloid-polymer mixtures show phase separation due to the depletion effect. The strategy to overcome this depletion demixing was to prepare surface-modified colloidal particles, which can be blended with linear polymer chains homogeneous. A successful synthesis strategy for the preparation of hairy nanospheres was developed by grafting polystyrene macromonomer chains onto polyorganosiloxane microgels. The number of hairs per particle with a core radius of approximately 10nm exceeded 150 hairs in all cases. The molecular weight of the hairs variied between 4000-18000g/mol.The compatibility of these hairy spheres mixed with linear polymer chains was investigated by AFM, TEM and SAXS. Homogeneous mixtures were found if the molecular weight of the polymer hairs on the particle surface is at least as large as the molecular weight of the matrix chains. If the chains are much shorter than the hairs, the colloidal hair corona is strongly swollen by the matrix polymer, leading to a long-range soft interparticle repulsion ('wet brush'). If hairs and chains are comparable in length, the corona shows much less volume swelling, leading to a short-range repulsive potential similar to hard sphere systems ('dry brush'). Polymerketten und Kolloidpartikel entmischen aufgrund von Depletion-Wechselwirkungen. Diese entropisch bedingte Entmischung konnte durch das Ankoppeln von Polymerhaaren verschiedenen Molekulargewichts auf die Kugeloberflächen der Kolloide bis zu hohen Konzentrationen vermieden werden. Zur Darstellung sphärischer Bürsten und haariger Tracerpartikel wurde eine neue Synthesestrategie ausgearbeitet und erfolgreich umgesetzt.Das Kompatibilitätsverhalten dieser sphärischen Bürsten in der Schmelze von Polymerketten als Matrix wurde mittels Elektronenmikroskopie und Kleinwinkelröntgenstreuung untersucht. Die Mischungen setzten sich aus sphärischen Bürsten und Matrixketten mit unterschiedlichen Molekulargewichten zusammen.Es zeigte sich, daß die Mischbarkeit entschieden durch das Verhältnis von Haarlänge zu Länge der Matrixketten beeinflußt wird.Aus den Untersuchungen des Relaxationsverhaltens mittels Rheologie und SAXS ergibt sich, daß das Konzept der 'dry brush'- und 'wet brush'-Systeme auf diese Mischungen übertragbar ist. Die Volumenquellung der Haarcorona durch die Matrixketten ist, wie die Experimente gezeigt haben, bereits im Fall von Polymeren mit relativ niedrigen Molekulargewichten zu beobachten. Sie ist umso stärker ausgeprägt, je größer das Längenverhältnis zwischen Polymerhaaren und Matrixketten ist. Die Quellung bedeutet eine Vergrößerung des effektiven Radius der Partikel und entspricht somit einer Erhöhung des effektiven Volumenbruchs. Dies führt zur Ausbildung einer höheren Ordnung und zu einem Einfrieren der Relaxation dieser strukturellen Ordnung führt.

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Next generation electronic devices have to guarantee high performance while being less power-consuming and highly reliable for several application domains ranging from the entertainment to the business. In this context, multicore platforms have proven the most efficient design choice but new challenges have to be faced. The ever-increasing miniaturization of the components produces unexpected variations on technological parameters and wear-out characterized by soft and hard errors. Even though hardware techniques, which lend themselves to be applied at design time, have been studied with the objective to mitigate these effects, they are not sufficient; thus software adaptive techniques are necessary. In this thesis we focus on multicore task allocation strategies to minimize the energy consumption while meeting performance constraints. We firstly devise a technique based on an Integer Linear Problem formulation which provides the optimal solution but cannot be applied on-line since the algorithm it needs is time-demanding; then we propose a sub-optimal technique based on two steps which can be applied on-line. We demonstrate the effectiveness of the latter solution through an exhaustive comparison against the optimal solution, state-of-the-art policies, and variability-agnostic task allocations by running multimedia applications on the virtual prototype of a next generation industrial multicore platform. We also face the problem of the performance and lifetime degradation. We firstly focus on embedded multicore platforms and propose an idleness distribution policy that increases core expected lifetimes by duty cycling their activity; then, we investigate the use of micro thermoelectrical coolers in general-purpose multicore processors to control the temperature of the cores at runtime with the objective of meeting lifetime constraints without performance loss.

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Il presente lavoro trae origine dagli obiettivi e dalle relative misure applicative della riforma dell’OCM zucchero del 2006 e nello specifico dal Piano nazionale per la razionalizzazione e riconversione della produzione bieticolo-saccarifera approvato dal MIPAF nel 2007. Lo studio riguarda la riconversione dello zuccherificio di Finale Emilia (MO), di appartenenza del Gruppo bieticolo-saccarifero Co.Pro.B, in un impianto di generazione di energia elettrica e termica che utilizza biomassa di origine agricola per la combustione diretta. L'alimentazione avviene principalmente dalla coltivazione dedicata del sorgo da fibra (Sorghum bicolor), integrata con risorse agro-forestali. Lo studio mostra la necessità di coltivazione di 4.400 ettari di sorgo da fibra con una produzione annua di circa 97.000 t di prodotto al 75% di sostanza secca necessari per l’alimentazione della centrale a biomassa. L’obiettivo é quello di valutare l’impatto della nuova coltura energetica sul comprensorio agricolo e sulla economia dell’impresa agricola. La metodologia adottata si basa sulla simulazione di modelli aziendali di programmazione lineare che prevedono l’inserimento del sorgo da fibra come coltura energetica nel piano ottimo delle aziende considerate. I modelli predisposti sono stati calibrati su aziende RICA al fine di riprodurre riparti medi reali su tre tipologie dimensionali rappresentative: azienda piccola entro i 20 ha, media da 20 a 50 ha e grande oltre i 50 ha. La superficie di entrata a livello aziendale, se rapportata alla rappresentatività delle aziende dell’area di studio, risulta insufficiente per soddisfare la richiesta di approvvigionamento dell’impianto a biomassa. Infatti con tale incremento la superficie di coltivazione nel comprensorio si attesta sui 2.500 ettari circa contro i 4.400 necessari alla centrale. Lo studio mostra pertanto che occorre un incentivo superiore, di circa 80-90 €/ha, per soddisfare la richiesta della superficie colturale a livello di territorio. A questi livelli, la disponibilità della coltura energetica sul comprensorio risulta circa 9.500 ettari.

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This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

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BACKGROUND: Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem. RESULTS: SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546. CONCLUSION: Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.

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BACKGROUND: We sought to characterize the impact that hepatitis C virus (HCV) infection has on CD4 cells during the first 48 weeks of antiretroviral therapy (ART) in previously ART-naive human immunodeficiency virus (HIV)-infected patients. METHODS: The HIV/AIDS Drug Treatment Programme at the British Columbia Centre for Excellence in HIV/AIDS distributes all ART in this Canadian province. Eligible individuals were those whose first-ever ART included 2 nucleoside reverse transcriptase inhibitors and either a protease inhibitor or a nonnucleoside reverse transcriptase inhibitor and who had a documented positive result for HCV antibody testing. Outcomes were binary events (time to an increase of > or = 75 CD4 cells/mm3 or an increase of > or = 10% in the percentage of CD4 cells in the total T cell population [CD4 cell fraction]) and continuous repeated measures. Statistical analyses used parametric and nonparametric methods, including multivariate mixed-effects linear regression analysis and Cox proportional hazards analysis. RESULTS: Of 1186 eligible patients, 606 (51%) were positive and 580 (49%) were negative for HCV antibodies. HCV antibody-positive patients were slower to have an absolute (P<.001) and a fraction (P = .02) CD4 cell event. In adjusted Cox proportional hazards analysis (controlling for age, sex, baseline absolute CD4 cell count, baseline pVL, type of ART initiated, AIDS diagnosis at baseline, adherence to ART regimen, and number of CD4 cell measurements), HCV antibody-positive patients were less likely to have an absolute CD4 cell event (adjusted hazard ratio [AHR], 0.84 [95% confidence interval [CI], 0.72-0.98]) and somewhat less likely to have a CD4 cell fraction event (AHR, 0.89 [95% CI, 0.70-1.14]) than HCV antibody-negative patients. In multivariate mixed-effects linear regression analysis, HCV antibody-negative patients had increases of an average of 75 cells in the absolute CD4 cell count and 4.4% in the CD4 cell fraction, compared with 20 cells and 1.1% in HCV antibody-positive patients, during the first 48 weeks of ART, after adjustment for time-updated pVL, number of CD4 cell measurements, and other factors. CONCLUSION: HCV antibody-positive HIV-infected patients may have an altered immunologic response to ART.

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Small-scale farmers in the Chipata District of Zambia rely on their farm fields to grow maize and groundnuts for food security. Cotton production and surplus food security crops are used to generate income to provide for their families. With increasing population pressure, available land has decreased and farmers struggle to provide the necessary food requirements and income to meet their family’s needs. The purpose of the study was to determine how a farmer can best allocate his land to produce maize, groundnuts and cotton when constrained by labor and capital resources to generate the highest potential for food security and financial gains. Data from the 2008-2009 growing season was compiled and analyzed using a linear programming model. The study determined that farmers make the most profit by allocating all additional land and resources to cotton after meeting their minimum food security requirements. The study suggests growing cotton is a beneficial practice for small-scale subsistence farmers to generate income when restricted by limited resources.

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While revenue management (RM) is traditionally considered a tool of service operations, RM shows considerable potential for application in manufacturing operations. The typical challenges in make-to-order manufacturing are fixed manufacturing capacities and a great variety in offered products, going along with pronounced fluctuations in demand and profitability. Since Harris and Pinder in the mid-90s, numerous papers have furthered the understanding of RM theory in this environment. Nevertheless, results to be expected from applying the developed methods to a practical industry setting have yet to be reported. To this end, this paper investigates a possible application of RM at ThyssenKrupp VDM, leading to considerable improvements in several areas.

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Firms aim at assigning qualified and motivated people to jobs. Human resources managers often conduct assessment centers before making such personnel decisions. By means of an assessment center, the potential and skills of job applicants can be assessed more objectively. For the scheduling of such assessment centers, we present a formulation as a mixed-binary linear program and report on computational results for four real-life examples.

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Offset printing is a common method to produce large amounts of printed matter. We consider a real-world offset printing process that is used to imprint customer-specific designs on napkin pouches. The print- ing technology used yields a number of specific constraints. The planning problem consists of allocating designs to printing-plate slots such that the given customer demand for each design is fulfilled, all technologi- cal and organizational constraints are met and the total overproduction and setup costs are minimized. We formulate this planning problem as a mixed-binary linear program, and we develop a multi-pass matching-based savings heuristic. We report computational results for a set of problem instances devised from real-world data.