A common problem when running Web-based applications is how to scale-up the database. The solution to this problem usually involves having a smart Database Administrator determine how to spread the database tables out amongst computers that will work in parallel. Laying out database tables across multiple machines so they can act together as a single efficient database is hard. Automated methods are needed to help eliminate the time required for database administrators to create optimal configurations. There are four operators that we consider that can create a search space of possible database layouts: 1) denormalizing, 2) horizontally partitioning, 3) vertically partitioning, and 4) fully replicating. Textbooks offer general advice that is useful for dealing with extreme cases - for instance you should fully replicate a table if the level of insert to selects is close to zero. But even this seemingly obvious statement is not necessarily one that will lead to a speed up once you take into account that some nodes might be a bottle neck. There can be complex interactions between the 4 different operators which make it even more difficult to predict what the best thing to do is. Instead of using best practices to do database layout, we need a system that collects empirical data on when these 4 different operators are effective. We have implemented a state based search technique to try different operators, and then we used the empirically measured data to see if any speed up occurred. We recognized that the costs of creating the physical database layout are potentially large, but it is necessary since we want to know the "Ground Truth" about what is effective and under what conditions. After creating a dataset where these four different operators have been applied to make different databases, we can employ machine learning to induce rules to help govern the physical design of the database across an arbitrary number of computer nodes. This learning process, in turn, would allow the database placement algorithm to get better over time as it trains over a set of examples. What this algorithm calls for is that it will try to learn 1) "What is a good database layout for a particular application given a query workload?" and 2) "Can this algorithm automatically improve itself in making recommendations by using machine learned rules to try to generalize when it makes sense to apply each of these operators?" There has been considerable research done in parallelizing databases where large amounts of data are shipped from one node to another to answer a single query. Sometimes the costs of shipping the data back and forth might be high, so in this work we assume that it might be more efficient to create a database layout where each query can be answered by a single node. To make this assumption requires that all the incoming query templates are known beforehand. This requirement can easily be satisfied in the case of a Web-based application due to the characteristic that users typically interact with the system through a web interface such as web forms. In this case, unseen queries are not necessarily answerable, without first possibly reconstructing the data on a single machine. Prior knowledge of these exact query templates allows us to select the best possible database table placements across multiple nodes. But in the case of trying to improve the efficiency of a Web-based application, a web site provider might feel that they are willing to suffer the inconvenience of not being able to answer an arbitrary query, if they are in turn provided with a system that runs more efficiently.

Energy saving and fuel consumption reduction techniques are among the principal interests for both academic institutions and industries, in particular, system optimization and hybridization. This paper presents a new hydraulic hybrid system layout for mobile machinery implemented on a middle size excavator. The hybridization procedure took advantage of a dynamic programming (DP) algorithm, which was also utilized for the hybrid components dimensioning and control strategy definition. A dedicated experimental activity on test bench was performed on the main components of the energy recovery system (ERS). The JCMAS working cycle was considered as the reference test for a fuel consumption comparison between the standard and the hybrid excavator. A fuel saving up to 8% on the JCMAS cycle, and up to 11% during the digging cycle, has been allowed by the proposed hybrid system.

A new integrated layout optimization method is proposed here for the design of multi-component systems. By introducing movable components into the design domain, the components layout and the supporting structural topology are optimized simultaneously. The developed design procedure mainly consists of three parts: (i). Introduction of non-overlap constraints between components. The Finite Circle Method (FCM) is used to avoid the components overlaps and also overlaps between components and the design domain boundaries. It proceeds by approximating geometries of components and the design domain with numbers of circles. The distance constraints between the circles of different components are then imposed as non-overlap constraints. (ii). Layout optimization of the components and supporting structure. Locations and orientations of the components are assumed as geometrical design variables for the optimal placement. Topology design variables of the supporting structure are defined by the density points. Meanwhile, embedded meshing techniques are developed to take into account the finite element mesh change caused by the component movements. Moreover, to account for the complicated requirements from aerospace structural system designs, design-dependent loads related to the inertial load or the structural self-weight and the design constraint related to the system gravity center position are taken into account in the problem formulation. (iii). Consistent material interpolation scheme between element stiffness and inertial load. The common SIMP material interpolation model is improved to avoid the singularity of localized deformation due to the presence of design dependent loading when the element stiffness and the involved inertial load are weakened with the element material removal. Finally, to validate the proposed design procedure, a variety of multi-component system layout design problems are tested and solved on account of inertia loads and gravity center position constraint.

The present study addresses an optimization strategy for maximizing the structural ductility of Fiber Reinforced Concrete (FRC) with long textile fibers. Due to material brittleness of both concrete and fiber in addition to complex interfacial behavior between above constituents the structural response of FRC is highly nonlinear. Consideration of this material nonlinearity including interface is mandatory to deal with this kind of composite. In the present contribution three kinds of optimization strategies based on a damage formulation are described. The performance of the proposed method is demonstrated by a series of numerical examples; it is verified that the ductility can be substantially improved.

Losses for wake effects in offshore wind farms represent about 10% to 20% of the park annual energy production. Several analytical wake models have been developed and implemented to predict the power deficit of a wake-affected wind turbine. Validating and parameterizing the wake models available in the industry is essential to better predict the wake losses and thus maximize the energy yield of future offshore developments. In this study, a wake model validation is undertaken for the three models available in the commercial software WindSim. Data from Horns Rev wind farm is used to that purpose. Next, the models that show the best agreement with the observations are parameterized to better describe the power losses of a future offshore wind farm at Bockstigen. To finish with, an optimization sensitivity study is carried out and a final optimal layout is determined according to the seabed depth.

Millimeter-wave has been a medium for automotive, sensor, and defense applications for a long time. But, a fully integrated silicon-based transceiver at 60 GHz or higher frequencies has become the driving force for recent research activities in integrated millimeter-wave (MMW) circuit designs. However, no integrated compact high-performance millimeter-wave system can be designed without accurate estimation and optimization of layout parasitics. In this dissertation, the estimation, modeling and optimization of parasitic effects as well as the verification of extraction methodologies for RF/MMW applications are investigated. Different circuit design- and layout-examples are considered with stress on the inclusion and optimization of wire/interconnect parasitics. A novel methodology is proposed to reduce the number of design-passes and to include layout parasitics in the design optimization procedure. An automated verification procedure for existing parasitic extraction tools is developed. Neural-network-based models are used to demonstrate the effectiveness of artificial intelligence techniques for characterizing parasitic components. The parasitic sensitivities for selected millimeter-wave circuits are demonstrated, and a parasitic benchmarking procedure is developed using MMW oscillators. Measurement results of several circuits that are implemented in state-of-the-art CMOS and SiGe-BiCMOS processes are used to demonstrate the role of parasitics and the systematic design methodology including parasitics.

The diploma work is focused on a store layout optimization and the related areas. The work is divided into four parts where the first three parts described the theoretical thesis. The first chapter is about the marketing theory -- a customer's behavioral rules in a retail store and a correct store layout. The second chapter is based on the logistics theory and describes the methods of a range of goods categorization according to the different views. The third chapter is focused on the operations research theory and the assignment problem's models. The last chapter describes in detail a real example workflow -- the store layout optimization for Linde Gas Company. The objective is identification of the lucrative areas in the stores, the sold range of goods analysis and the creation of the store layout which will respect a customer's behavioral rules and which will also promote the sales of the selected goods.

The master Thesis deals with the layout optimization of two production lines in the company Frauenthal Automotive Hustopece Ltd. Thanks to this design, reduction of needed operators can be realized and design is linked with process time analyzation. Also a new design of working tools is created, which should help operator and improve ergonomic of workplace. The last part discusses about implementation costs of new design.

Energy saving and fuel consumption reduction techniques are among the principal interests for both academic institutions and industries, in particular, system optimization and hybridization. This paper presents a new hydraulic hybrid system layout for mobile machinery implemented on a middle size excavator. The hybridization procedure took advantage of a dynamic programming (DP) algorithm, which was also utilized for the hybrid components dimensioning and control strategy definition. A dedicated experimental activity on test bench was performed on the main components of the energy recovery system (ERS). The JCMAS working cycle was considered as the reference test for a fuel consumption comparison between the standard and the hybrid excavator. A fuel saving up to 8% on the JCMAS cycle, and up to 11% during the digging cycle, has been allowed by the proposed hybrid system.

To utilize space better, warehouses stack their products on top of each other. This increases the risk of injury for workers when storing and retrieving the products. Some warehouses counteract this by using robots to retrieve products to a picking area where a human worker picks the products needed to fulfill an order. This means that it is important for the robots to be effective when retrieving products to reduce the time the worker spends waiting in the picking area. This thesis focuses on the grouping of products in the containers when they are stored in the warehouse. The robots will then retrieve one container at a time and if the grouping of products is done correctly this should decrease the number of retrievals required to fulfill an order. In order to make the decision on which products to group together, an application was developed that data mined previous orders that the warehouse had received in an attempt to extract information about the products. With the help of this information the application then suggests different product layouts that focus on different goals when they are created. The different layouts are then compared against each other in order to determine which layout technique produces the best results. This algorithm has been named the PLO-algorithm. The results showed that when a product is placed with the PLO-algorithm, the most important aspect to consider is the relations it has with the other products it is grouped with. The results also showed that data mining orders that are too old can have a negative impact on the result if not handled correctly. The results also showed that when constructing the warehouse you should try to avoid restrictions that affect which products can be placed together as much as possible since these restrictions can impact the effectiveness of the warehouse in a negative way. The thesis draws the conclusion that there is a clear gain in effectiveness for warehouses to have a planed layout for their products. It is recommended to data mine previous orders to extract relations between the products if possible since this piece of information showed the best results in this thesis. It is also in the warehouse best interest to avoid as many restrictions as possible that affect which products can be placed together since this can impact the results in a negative way. It is also beneficial to not include data that is too old in the data mining since this can impact the results in a negative way if not handled correctly. / För att utnyttja sitt utrymme bättre staplar lagerhus sina produkter på höjden. Detta medför högre risker för personskada vid hämtning och lämning av produkter, en del lagerhus löser detta genom att använda sig av robotar som hämtar och lämnar produkterna i lagerhuset. Robotarna hämtar och lämnar produkterna i en plock zon där en mänsklig arbetare plockar de produkter som behövs för en order. Detta innebär att det är viktigt att robotarna är effektiva i sin hämtning av produkter för att minska väntetiden för arbetarna i plock zonen. I ett försök att effektivisera robotarna fokuserar denna avhandling på gruperingen av produkterna i behållarna. Detta innebär att beslutet om vilka produkter som ska grupperas tillsammans i samma behållare är viktig eftersom om rätt produkter lagras tillsammans så kommer detta minska antalet hämtningar och lämningar som krävs för att uppfylla en beställning. För att hjälpa till med detta beslut skapades en applikation som analyserade tidigare beställningar som varuhuset erhållit i ett försök att extrahera information om produkterna. Applikationen skapar sedan olika förslag på produkt placeringar där de olika förslagen fokuserar på olika mål för att undersöka vilket mål som är viktigast att fokusera på när en produkt ska placeras. Algoritmen i denna applikation har valts att kallas för PLO-algoritmen. Resultaten visade att när en produkt ska placeras med PLO-algoritmen så är det viktigt att gruppera produkten med produkter den har starka relationer till. Resultatet visade också att när data ska analyseras bör inte för gammal data analyseras då äldre relationer mellan produkter som inte stämmer längre kan påverka resultatet negativt om algoritmen ej hanterar detta på något sätt. Resultaten visade också att vid konstruktionen av lagerhuset bör restriktioner som begränsar hur produkter kan placeras, undvikas om möjligt då dessa kan påverka lagerhusets effektivitet negativt. Slutsatsen som kan dras är att ett lagerhus kan tjäna väldigt mycket på att ha en plan när de bestämmer hur deras produkter ska placeras. Om det finns möjlighet att analysera tidigare beställningar efter relationer mellan produkter så är detta rekommenderat då det visade bäst resultat i denna undersökning. Det är även till lagerhusets fördel att försöka undvika restriktioner på deras lagersystem när det byggs eftersom det möjliggör för fler kombinationer när produkterna ska grupperas. Till sist så visar avhandlingen att med datan som användes att det var fördelaktigt att inte göra analys på för gammal data, då detta ger sämre resultat.