An application of combinatorial optimization in the printing industry

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.

Applying the fuzzy analytical hierarchy process in digital marketing

The fuzzy analytical network process (FANP) is introduced as a potential multi-criteria-decision-making (MCDM) method to improve digital marketing management endeavors. Today’s information overload makes digital marketing optimization, which is needed to continuously improve one’s business, increasingly difficult. The proposed FANP framework is a method for enhancing the interaction between customers and marketers (i.e., involved stakeholders) and thus for reducing the challenges of big data. The presented implementation takes realities’ fuzziness into account to manage the constant interaction and continuous development of communication between marketers and customers on the Web. Using this FANP framework, the marketers are able to increasingly meet the varying requirements of their customers. To improve the understanding of the implementation, advanced visualization methods (e.g., wireframes) are used.

Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations

Multi-objective optimization algorithms aim at finding Pareto-optimal solutions. Recovering Pareto fronts or Pareto sets from a limited number of function evaluations are challenging problems. A popular approach in the case of expensive-to-evaluate functions is to appeal to metamodels. Kriging has been shown efficient as a base for sequential multi-objective optimization, notably through infill sampling criteria balancing exploitation and exploration such as the Expected Hypervolume Improvement. Here we consider Kriging metamodels not only for selecting new points, but as a tool for estimating the whole Pareto front and quantifying how much uncertainty remains on it at any stage of Kriging-based multi-objective optimization algorithms. Our approach relies on the Gaussian process interpretation of Kriging, and bases upon conditional simulations. Using concepts from random set theory, we propose to adapt the Vorob’ev expectation and deviation to capture the variability of the set of non-dominated points. Numerical experiments illustrate the potential of the proposed workflow, and it is shown on examples how Gaussian process simulations and the estimated Vorob’ev deviation can be used to monitor the ability of Kriging-based multi-objective optimization algorithms to accurately learn the Pareto front.

Optimization of Optical Follow-up Strategies Based on Covariance Analysis

An in-depth study, using simulations and covariance analysis, is performed to identify the optimal sequence of observations to obtain the most accurate orbit propagation. The accuracy of the results of an orbit determination/ improvement process depends on: tracklet length, number of observations, type of orbit, astrometric error, time interval between tracklets and observation geometry. The latter depends on the position of the object along its orbit and the location of the observing station. This covariance analysis aims to optimize the observation strategy taking into account the influence of the orbit shape, of the relative object-observer geometry and the interval between observations.

EPANET Input Files of New York tunnels and Pacific City used in a metamodel-based optimization study

Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

In-loop Feature Tracking for Structure and Motion with Out-of-core Optimization

In this paper, a novel and approach for obtaining 3D models from video sequences captured with hand-held cameras is addressed. We define a pipeline that robustly deals with different types of sequences and acquiring devices. Our system follows a divide and conquer approach: after a frame decimation that pre-conditions the input sequence, the video is split into short-length clips. This allows to parallelize the reconstruction step which translates into a reduction in the amount of computational resources required. The short length of the clips allows an intensive search for the best solution at each step of reconstruction which robustifies the system. The process of feature tracking is embedded within the reconstruction loop for each clip as opposed to other approaches. A final registration step, merges all the processed clips to the same coordinate frame

Laser-fired contact optimization in c-Si solar cells

In this work we study the optimization of laser-fired contact (LFC) processing parameters, namely laser power and number of pulses, based on the electrical resistance measurement of an aluminum single LFC point. LFC process has been made through four passivation layers that are typically used in c-Si and mc-Si solar cell fabrication: thermally grown silicon oxide (SiO2), deposited phosphorus-doped amorphous silicon carbide (a-SiCx/H(n)), aluminum oxide (Al2O3) and silicon nitride (SiNx/H) films. Values for the LFC resistance normalized by the laser spot area in the range of 0.65–3 mΩ cm2 have been obtained

Sputter optimization of AlN on diamond substrates for high frequency SAW resonators

The AlN/diamond structure is an attractive combination for SAW devices and its application at high frequencies. In this work, the synthesis of AlN thin films by reactive sputtering has been optimized on diamond substrates in order to process high frequency devices. Polished microcrystalline and as-grown nanocrystalline diamond substrates have been used to deposit AlN of different thickness under equal sputtering conditions. For the smoother substrates, the FWHM of the rocking curve of the (002) AlN peak varies from 3.8° to 2.7° with increasing power. SAW one port resonators have been fabricated on these films, whose electrical characterization (in terms of S11 parameters) is reported.

Optimization of laser-firing processes for silicon-heterojunction solar-cell back contacts

One of the key steps to achieve high efficiencies in amorphous/crystalline silicon photovoltaic structures is to design low-ohmic-resistance backcontacts with good passivation in the rear part of the cell. A well known approach to achieve this goal is to use laser-fired contact (LFC) processes in which a metal layer is fired through the dielectric to define good contacts with the semiconductor. However, and despite the fact that this approach has demonstrated to be extremely successful, there is still enough room for process improvement with an appropriate optimization. In this paper, a study focused on the optimal adjustment of the irradiation parameters to produce laser-fired contacts in a-Si:H/c-Si heterojunctionsolarcells is presented. We used samples consisting of crystalline-silicon (c-Si) wafers together with a passivation layer of intrinsic hydrogenated amorphous silicon (a-Si:H(i)) deposited by plasma-enhanced chemical deposition (PECVD). Then, an aluminum layer was evaporated on both sides, the thickness of this layer varied from 0.2 to 1 μm in order to identify the optimal amount of Al required to create an appropriate contact. A q-switched Nd:YVO4laser source, λ = 532 nm, was used to locally fire the aluminum through the thin a-Si:H(i)-layers to form the LFC. The effects of laser fluences were analyzed using a comprehensive morphological and electrical characterization.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks (WSNs) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of WSNs facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers (DCs). The high economical and environmental impact of the energy consumption in DCs requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of WSNs: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of DCs: energy-optimal workload assignment policies in heterogeneous DCs, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

GreenDisc: a HW/SW energy optimization framework in globally distributed computation

In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the DCs that process the data provided by the WSNs.

Optimization of the silicon subcell for III-V on silicon multijunction solar cells: key differences with conventional silicon technology

Dual-junction solar cells formed by a GaAsP or GaInP top cell and a silicon (Si) bottom cell seem to be attractive candidates to materialize the long sought-for integration of III-V materials on Si for photovoltaic (PV) applications. Such integration would offer a cost breakthrough for PV technology, unifying the low cost of Si and the efficiency potential of III-V multijunction solar cells. The optimization of the Si solar cells properties in flat-plate PV technology is well-known; nevertheless, it has been proven that the behavior of Si substrates is different when processed in an MOVPE reactor In this study, we analyze several factors influencing the bottom subcell performance, namely, 1) the emitter formation as a result of phosphorus diffusion; 2) the passivation quality provided by the GaP nucleation layer; and 3) the process impact on the bottom subcell PV properties.

Tool wear monitoring using neuro-fuzzy techniques: a comparative study in a turning process

Tool wear detection is a key issue for tool condition monitoring. The maximization of useful tool life is frequently related with the optimization of machining processes. This paper presents two model-based approaches for tool wear monitoring on the basis of neuro-fuzzy techniques. The use of a neuro-fuzzy hybridization to design a tool wear monitoring system is aiming at exploiting the synergy of neural networks and fuzzy logic, by combining human reasoning with learning and connectionist structure. The turning process that is a well-known machining process is selected for this case study. A four-input (i.e., time, cutting forces, vibrations and acoustic emissions signals) single-output (tool wear rate) model is designed and implemented on the basis of three neuro-fuzzy approaches (inductive, transductive and evolving neuro-fuzzy systems). The tool wear model is then used for monitoring the turning process. The comparative study demonstrates that the transductive neuro-fuzzy model provides better error-based performance indices for detecting tool wear than the inductive neuro-fuzzy model and than the evolving neuro-fuzzy model.

Optimización de la composición del hueco de fachada en materia de eficiencia energética. Propuesta de indicador como herramienta para el análisis integral del elemento acristalado = Energy performance optimization of window systems. Proposal of an indicator as a tool for an integrated analysis of glazing

La hipótesis de esta tesis es: "La optimización de la ventana considerando simultáneamente aspectos energéticos y aspectos relativos a la calidad ambiental interior (confort higrotérmico, lumínico y acústico) es compatible, siempre que se conozcan y consideren las sinergias existentes entre ellos desde las primeras fases de diseño". En la actualidad se desconocen las implicaciones de muchas de las decisiones tomadas en torno a la ventana; para que su eficiencia en relación a todos los aspectos mencionados pueda hacerse efectiva es necesaria una herramienta que aporte más información de la actualmente disponible en el proceso de diseño, permitiendo así la optimización integral, en función de las circunstancias específicas de cada proyecto. En la fase inicial de esta investigación se realiza un primer acercamiento al tema, a través del estado del arte de la ventana; analizando la normativa existente, los componentes, las prestaciones, los elementos experimentales y la investigación. Se observa que, en ocasiones, altos requisitos de eficiencia energética pueden suponer una disminución de las prestaciones del sistema en relación con la calidad ambiental interior, por lo que surge el interés por integrar al análisis energético aspectos relativos a la calidad ambiental interior, como son las prestaciones lumínicas y acústicas y la renovación de aire. En este punto se detecta la necesidad de realizar un estudio integral que incorpore los distintos aspectos y evaluar las sinergias que se dan entre las distintas prestaciones que cumple la ventana. Además, del análisis de las soluciones innovadoras y experimentales se observa la dificultad de determinar en qué medida dichas soluciones son eficientes, ya que son soluciones complejas, no caracterizadas y que no están incorporadas en las metodologías de cálculo o en las bases de datos de los programas de simulación. Por lo tanto, se plantea una segunda necesidad, generar una metodología experimental para llevar a cabo la caracterización y el análisis de la eficiencia de sistemas innovadores. Para abordar esta doble necesidad se plantea la optimización mediante una evaluación del elemento acristalado que integre la eficiencia energética y la calidad ambiental interior, combinando la investigación teórica y la investigación experimental. En el ámbito teórico, se realizan simulaciones, cálculos y recopilación de información de distintas tipologías de hueco, en relación con cada prestación de forma independiente (acústica, iluminación, ventilación). A pesar de haber partido con un enfoque integrador, resulta difícil esa integración detectándose una carencia de herramientas disponible. En el ámbito experimental se desarrolla una metodología para la evaluación del rendimiento y de aspectos ambientales de aplicación a elementos innovadores de difícil valoración mediante la metodología teórica. Esta evaluación consiste en el análisis comparativo experimental entre el elemento innovador y un elemento estándar; para llevar a cabo este análisis se han diseñado dos espacios iguales, que denominamos módulos de experimentación, en los que se han incorporado los dos sistemas; estos espacios se han monitorizado, obteniéndose datos de consumo, temperatura, iluminancia y humedad relativa. Se ha realizado una medición durante un periodo de nueve meses y se han analizado y comparado los resultados, obteniendo así el comportamiento real del sistema. Tras el análisis teórico y el experimental, y como consecuencia de esa necesidad de integrar el conocimiento existente se propone una herramienta de evaluación integral del elemento acristalado. El desarrollo de esta herramienta se realiza en base al procedimiento de diagnóstico de calidad ambiental interior (CAI) de acuerdo con la norma UNE 171330 “Calidad ambiental en interiores”, incorporando el factor de eficiencia energética. De la primera parte del proceso, la parte teórica y el estado del arte, se obtendrán los parámetros que son determinantes y los valores de referencia de dichos parámetros. En base a los parámetros relevantes obtenidos se da forma a la herramienta, que consiste en un indicador de producto para ventanas que integra todos los factores analizados y que se desarrolla según la Norma UNE 21929 “Sostenibilidad en construcción de edificios. Indicadores de sostenibilidad”. ABSTRACT The hypothesis of this thesis is: "The optimization of windows considering energy and indoor environmental quality issues simultaneously (hydrothermal comfort, lighting comfort, and acoustic comfort) is compatible, provided that the synergies between these issues are known and considered from the early stages of design ". The implications of many of the decisions made on this item are currently unclear. So that savings can be made, an effective tool is needed to provide more information during the design process than the currently available, thus enabling optimization of the system according to the specific circumstances of each project. The initial phase deals with the study from an energy efficiency point of view, performing a qualitative and quantitative analysis of commercial, innovative and experimental windows. It is observed that sometimes, high-energy efficiency requirements may mean a reduction in the system's performance in relation to user comfort and health, that's why there is an interest in performing an integrated analysis of indoor environment aspects and energy efficiency. At this point a need for a comprehensive study incorporating the different aspects is detected, to evaluate the synergies that exist between the various benefits that meet the window. Moreover, from the analysis of experimental and innovative windows, a difficulty in establishing to what extent these solutions are efficient is observed; therefore, there is a need to generate a methodology for performing the analysis of the efficiency of the systems. Therefore, a second need arises, to generate an experimental methodology to perform characterization and analysis of the efficiency of innovative systems. To address this dual need, the optimization of windows by an integrated evaluation arises, considering energy efficiency and indoor environmental quality, combining theoretical and experimental research. In the theoretical field, simulations and calculations are performed; also information about the different aspects of indoor environment (acoustics, lighting, ventilation) is gathered independently. Despite having started with an integrative approach, this integration is difficult detecting lack available tools. In the experimental field, a methodology for evaluating energy efficiency and indoor environment quality is developed, to be implemented in innovative elements which are difficult to evaluate using a theoretical methodology This evaluation is an experimental comparative analysis between an innovative element and a standard element. To carry out this analysis, two equal spaces, called experimental cells, have been designed. These cells have been monitored, obtaining consumption, temperature, luminance and relative humidity data. Measurement has been performed during nine months and results have been analyzed and compared, obtaining results of actual system behavior. To advance this optimization, windows have been studied from the point of view of energy performance and performance in relation to user comfort and health: thermal comfort, acoustic comfort, lighting comfort and air quality; proposing the development of a methodology for an integrated analysis including energy efficiency and indoor environment quality. After theoretical and experimental analysis and as a result of the need to integrate existing knowledge, a comprehensive evaluation procedure for windows is proposed. This evaluation procedure is developed according to the UNE 171330 "Indoor Environmental Quality", also incorporating energy efficiency and cost as factors to evaluate. From the first part of the research process, outstanding parameters are chosen and reference values of these parameters are set. Finally, based on the parameters obtained, an indicator is proposed as windows product indicator. The indicator integrates all factors analyzed and is developed according to ISO 21929-1:2011"Sustainability in building construction. Sustainability indicators. Part 1: Framework for the development of indicators and a core set of indicators for buildings".