Selection of Switching Sites in All-Optical Nework Topology Design

In this paper, we consider the problem of topology design for optical networks. We investigate the problem of selecting switching sites to minimize total cost of the optical network. The cost of an optical network can be expressed as a sum of three main factors: the site cost, the link cost, and the switch cost. To the best of our knowledge, this problem has not been studied in its general form as investigated in this paper. We present a mixed integer quadratic programming (MIQP) formulation of the problem to find the optimal value of the total network cost. We also present an efficient heuristic to approximate the solution in polynomial time. The experimental results show good performance of the heuristic. The value of the total network cost computed by the heuristic varies within 2% to 21% of its optimal value in the experiments with 10 nodes. The total network cost computed by the heuristic for 51% of the experiments with 10 node network topologies varies within 8% of its optimal value. We also discuss the insight gained from our experiments.

Cost and energy density of diet in Brazil, 2008-2009

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.

On response time reduction of electrothermomechanical MEMS using topology optimization

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.

Design methodology of piezoelectric energy-harvesting skin using topology optimization

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

Development of heat sink device by using topology optimization

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.

Variability-tolerant High-reliability Multicore Platforms

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.

Riconversione degli impianti saccariferi per la valorizzazione della filiera agro-energetica: analisi di impatto sul comprensorio agricolo

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.

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

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.

SNA--a toolbox for the stoichiometric analysis of metabolic networks

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.

Farmer land allocation for maize, groundnut and cotton production in Chipata District, Eastern Province, Zambia

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.

Entwicklung eines Dispositionsleitstandes zur Bestimmung optimaler Torbelegungen in Stückgutspeditionsanlagen

Im operativen Betrieb einer Stückgutspeditionsanlage entscheidet der Betriebslenker bzw. der Disponent in einem ersten Schritt darüber, an welche Tore die Fahrzeuge zur Be- und Entladung andocken sollen. Darüber hinaus muss er für jede Tour ein Zeitfenster ausweisen innerhalb dessen sie das jeweilige Tor belegt. Durch die örtliche und zeitliche Fahrzeug-Tor-Zuordnung wird der für den innerbetrieblichen Umschlagprozess erforderliche Ressourcenaufwand in Form von zu fahrenden Wegstrecken oder aber Gabelstaplerstunden bestimmt. Ein Ziel der Planungsaufgabe ist somit, die Zuordnung der Fahrzeuge an die Tore so vorzunehmen, dass dabei minimale innerbetriebliche Wegstrecken entstehen. Dies führt zu einer minimalen Anzahl an benötigten Umschlagmittelressourcen. Darüber hinaus kann es aber auch zweckmäßig sein, die Fahrzeuge möglichst früh an die Tore anzudocken. Jede Tour verfügt über einen individuellen Fahrplan, der Auskunft über den Ankunftszeitpunkt sowie den Abfahrtszeitpunkt der jeweiligen Tour von der Anlage gibt. Nur innerhalb dieses Zeitfensters darf der Disponent die Tour einem der Tore zuweisen. Geschieht die Zuweisung nicht sofort nach Ankunft in der Anlage, so muss das Fahrzeug auf einer Parkfläche warten. Eine Minimierung der Wartezeiten ist wünschenswert, damit das Gelände der Anlage möglichst nicht durch zuviele Fahrzeuge gleichzeitig belastet wird. Es kann vor allem aber auch im Hinblick auf das Reservieren der Tore für zeitkritische Touren sinnvoll sein, Fahrzeuge möglichst früh abzufertigen. Am Lehrstuhl Verkehrssysteme und -logistik (VSL) der Universität Dortmund wurde die Entscheidungssituation im Rahmen eines Forschungsprojekts bei der Stiftung Industrieforschung in Anlehnung an ein zeitdiskretes Mehrgüterflussproblem mit unsplittable flow Bedingungen modelliert. Die beiden Zielsetzungen wurden dabei in einer eindimensionalen Zielfunktion integriert. Das resultierende Mixed Integer Linear Programm (MILP) wurde programmiert und für mittlere Szenarien durch Eingabe in den Optimization Solver CPlex mit dem dort implementierten exakten Branch-and-Cut Verfahren gelöst. Parallel wurde im Rahmen einer Kooperation zwischen dem Lehrstuhl VSL und dem Unternehmen hafa Docking Systems, einem der weltweit führenden Tor und Rampenhersteller, für die gleiche Planungsaufgabe ein heuristisches Scheduling Verfahren sowie ein Dispositionsleitstand namens LoadDock Navigation entwickelt. Der Dispositionsleitstand dient der optimalen Steuerung der Torbelegungen in logistischen Anlagen. In dem Leitstand wird planerische Intelligenz in Form des heuristischen Schedulingverfahrens, technische Neuerungen in der Rampentechnik in Form von Sensoren und das Expertenwissen des Disponenten in einem Tool verbunden. Das mathematische Modell sowie der Prototyp mit der integrierten Heuristik werden im Rahmen dieses Artikels vorgestellt.

Revenue Management in Make-To-Order Manufacturing: Case Study of Capacity Control at ThyssenKrupp VDM

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.

Optimal Scheduling of Work-Content-Constrained Projects

The execution of a project requires resources that are generally scarce. Classical approaches to resource allocation assume that the usage of these resources by an individual project activity is constant during the execution of that activity; in practice, however, the project manager may vary resource usage over time within prescribed bounds. This variation gives rise to the project scheduling problem which consists in allocating the scarce resources to the project activities over time such that the project duration is minimized, the total number of resource units allocated equals the prescribed work content of each activity, and various work-content-related constraints are met. We formulate this problem for the first time as a mixed-integer linear program. Our computational results for a standard test set from the literature indicate that this model outperforms the state-of-the-art solution methods for this problem.

Scheduling in service systems: an application in the event-tourism industry

This paper deals with an event-bus tour booked by Bollywood film fans. During the tour, the participants visit selected locations of famous Bollywood films at various sites in Switzerland. Moreover, the tour includes stops for lunch and shopping. Each day, up to five buses operate the tour; for organizational reasons, two or more buses cannot stay at the same location simultaneously. The planning problem is how to compute a feasible schedule for each bus such that the total waiting time (primary objective) and the total travel time (secondary objective) are minimized. We formulate this problem as a mixed-integer linear program, and we report on computational results obtained with the Gurobi solver.

Measured daily precipitation sums over Central Sulawesi for the period 1981-1999

Data compiled within the IMPENSO project. The Impact of ENSO on Sustainable Water Management and the Decision-Making Community at a Rainforest Margin in Indonesia (IMPENSO), http://www.gwdg.de/~impenso, was a German-Indonesian research project (2003-2007) that has studied the impact of ENSO (El Nino-Southern Oscillation) on the water resources and the agricultural production in the PALU RIVER watershed in Central Sulawesi. ENSO is a climate variability that causes serious droughts in Indonesia and other countries of South-East Asia. The last ENSO event occurred in 1997. As in other regions, many farmers in Central Sulawesi suffered from reduced crop yields and lost their livestock. A better prediction of ENSO and the development of coping strategies would help local communities mitigate the impact of ENSO on rural livelihoods and food security. The IMPENSO project deals with the impact of the climate variability ENSO (El Niño Southern Oscillation) on water resource management and the local communities in the Palu River watershed of Central Sulawesi, Indonesia. The project consists of three interrelated sub-projects, which study the local and regional manifestation of ENSO using the Regional Climate Models REMO and GESIMA (Sub-project A), quantify the impact of ENSO on the availability of water for agriculture and other uses, using the distributed hydrological model WaSiM-ETH (Sub-project B), and analyze the socio-economic impact and the policy implications of ENSO on the basis of a production function analysis, a household vulnerability analysis, and a linear programming model (Sub-project C). The models used in the three sub-projects will be integrated to simulate joint scenarios that are defined in collaboration with local stakeholders and are relevant for the design of coping strategies.