Esta tese integra dois problemas de áreas distintas e interdependentes intitulados de Sequenciamento Otimizado de Faturamento (SOF) e Sequenciamento Otimizado de Coleta (SOC). Abordados de forma disjunta pelos pesquisadores, o SOF refere-se a um problema de maximização do faturamento e o SOC consiste de uma variação do Order Batching and Sequencing Problem (OBSP). Fundamentados por pressupostos práticos e científicos, o SOF/SOC retratam o cotidiano dos processos de faturamento e picking de um típico Armazém de Distribuição (AM). No SOF a demanda é estocástica e os faturamentos ocorrem a partir de janelas de tempo variáveis ajustadas para evitar o tardiness mediante a priorização das datas de atendimento pela regra Earliest Due Date (EDD). No SOC o picking é manual e enquadra-se na categoria picker-to-parts (low level) com pick-and-sort utilizando um trolley que é transportado pelo operador ao longo das ruas do AM. Neste contexto, esta tese tem como objetivo desenvolver uma ferramenta de gestão que integre e apresente soluções otimizadas para o SOF/SOC. A perspectiva de integração do SOF/SOC dar-se-á mediante à formulação de dois Algoritmos Genéticos (AGs) nomeados de AG-SOF e AG-SOC. Assim, o enfoque desta pesquisa está na avaliação da eficácia prática do AG-SOF/AG-SOC em resolver problemas reais do SOF/SOC. A eficácia do AG-SOF é comparada à um Algoritmo Guloso Iterativo (AI-SOF) enquanto que a predileção pelo AG-SOC é justificada pela natureza NP-hard do SOC. As experimentações para problemas de diferentes níveis de complexidade demonstraram que os algoritmos satisfazem todas as regras, restrições e variáveis decisórias obtendo soluções de qualidade satisfatória para qualquer categoria do SOF/SOC. O AISOF/ AG-SOF lidam com as restrições de estoque e as possibilidades de faturar pedidos parciais para maximizar o Faturamento Total (FT). Apesar de obterem soluções com a mesma qualidade, o AI-SOF tem desempenho superior ao AG-SOF que é, em termos de Tempo de Processamento Computacional (TPC), limitado às categorias de médio porte do SOF. O AG-SOC é composto pela iteração de dois AGs (AGLOTE e AGPCV) que minimizam o Custo Total das Operações de Picking (CT). Logo, o AGLOTE agrupa os SKUs (Stock Keeping Units) dos diferentes pedidos em múltiplos lotes pela restrição de carga dos trolleys de forma a reduzir o Número de Viagens de Coleta (NVC) e define a sequência de coleta por meio de lotes prioritários para evitar o Atraso no Atendimento dos Pedidos (AAP). O AGPCV faz a roteirização dos lotes dentro do AM de modo que impeça a ocorrência de avarias aos SKUs frágeis e minimize a Distância Total das Rotas (DTR) e o Tempo Total de Picking (TTP). Evidenciou-se que para problemas de complexidade superior os lotes são mais homogêneos, nos quais o Desvio Padrão é pequeno e o Coeficiente de Variação é de 11,22% a 25,20% para a DTR. Para ambientes reais em que se utiliza janelas de tempo e logs de processamentos para lotes off-lines) a combinação do AI-SOF/AGSOC provê soluções otimizadas em tempo e qualidade satisfatória ao SOF/SOC. Em suma, esta pesquisa foi além das abordagens existentes para preencher um gap na literatura e prover uma importante contribuição à prática da otimização do SOF/SOC. É possível conclui que a integração do AI-SOF/AGSOC é capaz de maximizar o faturamento e melhorar a produtividade de forma a minimizar os tempos e custos operacionais de picking do AM. / This thesis integrates two problems from distinct and independent areas called Optimal Sequencing Billing (OSB) and Optimal Picking Sequencing (OPS). Studied separately by researchers, OBS refers to a billing maximization problem and OPS is a variation of the Order Batching and Sequencing Problem (OBSP). Based on practical and scientific assumptions, OSB/OPS portray the picking daily routine in a typical Distribution Warehouse (WA). In OSB, the demand is stochastic and billings occur based on variables time windows that are adjusted to avoid tardiness by prioritizing the service dates based on the Earliest Due Date (EDD) rule. In OPS, picking is manual and falls into the low-level picker-to-parts category, and it uses a trolley that is pushed by an employee along WA aisles. In this context, this thesis has the objective of developing a management tool that can integrate and provide optimal solutions for OSB/OPS. The perspective of integrating OSB/OPS can be achieved through the formulation of two Genetic Algorithms (GAs) called GA-OSB and GA-OPS. Therefore, the focus of this research is to assess GA-OSB/GA-OPS practical efficiency to solve actual OSB/OPS problems. GA-OSB efficiency is compared to an Iterative Greedy Algorithm (IA-OSB) whereas the preference for GA-OPS is justified by the NP-hard nature of OPS. Experiments for problems of different complexity levels showed that algorithms satisfy every rule, restriction and decision variable and provide satisfactory solutions for any OSB/OPS category. IA-OSB/GA-OSB deal with inventory restrictions and the possibility of billing partial orders to maximize Total Billing (TB). Although they also provide quality solutions, IA-OSB performance is better than GA-OSB performance which is limited to OSB medium-sized categories in terms of Computational Processing Time (CPT). GA-OPS comprises the iteration of two GAs (GABATCH and GATSP) that minimize the Total Cost of Picking Operations (TC). Therefore, GABATCH groups SKUs (Stock Keeping Units) of different orders into multiple lots according to trolley load restrictions so as to reduce the Number of Picking Travels (NPT). It also defines a picking sequence by means of priority lots to avoid Tardiness in Customer Orders (TCO). GATSP maps out the routes of lots inside the WA in order to prevent damages to fragile SKUs and to minimize Total Route Distance (TRD) as well as Total Picking Time (TPT). It was evidenced that, for problems of higher complexity, lots are more homogeneous where the Standard Deviation is small and the Coefficient of Variation (CV) ranges from 11.22% to 25.20% to the TRD. For actual environments where time windows and processing logs are used for off-line lots, the IA-OSB/GA-OPS integration provides optimal time solutions and satisfactory quality to OSB/OPS. In short, this research has gone beyond existing approaches to fill a gap in the literature and provide an important contribution to the practice of optimal OSB/OPS. It can be concluded that the integration of IA-OSB/GA-OPS can maximize billing and improve productivity in order to minimize picking operational time and costs in a WA.

Esta tese integra dois problemas de áreas distintas e interdependentes intitulados de Sequenciamento Otimizado de Faturamento (SOF) e Sequenciamento Otimizado de Coleta (SOC). Abordados de forma disjunta pelos pesquisadores, o SOF refere-se a um problema de maximização do faturamento e o SOC consiste de uma variação do Order Batching and Sequencing Problem (OBSP). Fundamentados por pressupostos práticos e científicos, o SOF/SOC retratam o cotidiano dos processos de faturamento e picking de um típico Armazém de Distribuição (AM). No SOF a demanda é estocástica e os faturamentos ocorrem a partir de janelas de tempo variáveis ajustadas para evitar o tardiness mediante a priorização das datas de atendimento pela regra Earliest Due Date (EDD). No SOC o picking é manual e enquadra-se na categoria picker-to-parts (low level) com pick-and-sort utilizando um trolley que é transportado pelo operador ao longo das ruas do AM. Neste contexto, esta tese tem como objetivo desenvolver uma ferramenta de gestão que integre e apresente soluções otimizadas para o SOF/SOC. A perspectiva de integração do SOF/SOC dar-se-á mediante à formulação de dois Algoritmos Genéticos (AGs) nomeados de AG-SOF e AG-SOC. Assim, o enfoque desta pesquisa está na avaliação da eficácia prática do AG-SOF/AG-SOC em resolver problemas reais do SOF/SOC. A eficácia do AG-SOF é comparada à um Algoritmo Guloso Iterativo (AI-SOF) enquanto que a predileção pelo AG-SOC é justificada pela natureza NP-hard do SOC. As experimentações para problemas de diferentes níveis de complexidade demonstraram que os algoritmos satisfazem todas as regras, restrições e variáveis decisórias obtendo soluções de qualidade satisfatória para qualquer categoria do SOF/SOC. O AISOF/ AG-SOF lidam com as restrições de estoque e as possibilidades de faturar pedidos parciais para maximizar o Faturamento Total (FT). Apesar de obterem soluções com a mesma qualidade, o AI-SOF tem desempenho superior ao AG-SOF que é, em termos de Tempo de Processamento Computacional (TPC), limitado às categorias de médio porte do SOF. O AG-SOC é composto pela iteração de dois AGs (AGLOTE e AGPCV) que minimizam o Custo Total das Operações de Picking (CT). Logo, o AGLOTE agrupa os SKUs (Stock Keeping Units) dos diferentes pedidos em múltiplos lotes pela restrição de carga dos trolleys de forma a reduzir o Número de Viagens de Coleta (NVC) e define a sequência de coleta por meio de lotes prioritários para evitar o Atraso no Atendimento dos Pedidos (AAP). O AGPCV faz a roteirização dos lotes dentro do AM de modo que impeça a ocorrência de avarias aos SKUs frágeis e minimize a Distância Total das Rotas (DTR) e o Tempo Total de Picking (TTP). Evidenciou-se que para problemas de complexidade superior os lotes são mais homogêneos, nos quais o Desvio Padrão é pequeno e o Coeficiente de Variação é de 11,22% a 25,20% para a DTR. Para ambientes reais em que se utiliza janelas de tempo e logs de processamentos para lotes off-lines) a combinação do AI-SOF/AGSOC provê soluções otimizadas em tempo e qualidade satisfatória ao SOF/SOC. Em suma, esta pesquisa foi além das abordagens existentes para preencher um gap na literatura e prover uma importante contribuição à prática da otimização do SOF/SOC. É possível conclui que a integração do AI-SOF/AGSOC é capaz de maximizar o faturamento e melhorar a produtividade de forma a minimizar os tempos e custos operacionais de picking do AM. / This thesis integrates two problems from distinct and independent areas called Optimal Sequencing Billing (OSB) and Optimal Picking Sequencing (OPS). Studied separately by researchers, OBS refers to a billing maximization problem and OPS is a variation of the Order Batching and Sequencing Problem (OBSP). Based on practical and scientific assumptions, OSB/OPS portray the picking daily routine in a typical Distribution Warehouse (WA). In OSB, the demand is stochastic and billings occur based on variables time windows that are adjusted to avoid tardiness by prioritizing the service dates based on the Earliest Due Date (EDD) rule. In OPS, picking is manual and falls into the low-level picker-to-parts category, and it uses a trolley that is pushed by an employee along WA aisles. In this context, this thesis has the objective of developing a management tool that can integrate and provide optimal solutions for OSB/OPS. The perspective of integrating OSB/OPS can be achieved through the formulation of two Genetic Algorithms (GAs) called GA-OSB and GA-OPS. Therefore, the focus of this research is to assess GA-OSB/GA-OPS practical efficiency to solve actual OSB/OPS problems. GA-OSB efficiency is compared to an Iterative Greedy Algorithm (IA-OSB) whereas the preference for GA-OPS is justified by the NP-hard nature of OPS. Experiments for problems of different complexity levels showed that algorithms satisfy every rule, restriction and decision variable and provide satisfactory solutions for any OSB/OPS category. IA-OSB/GA-OSB deal with inventory restrictions and the possibility of billing partial orders to maximize Total Billing (TB). Although they also provide quality solutions, IA-OSB performance is better than GA-OSB performance which is limited to OSB medium-sized categories in terms of Computational Processing Time (CPT). GA-OPS comprises the iteration of two GAs (GABATCH and GATSP) that minimize the Total Cost of Picking Operations (TC). Therefore, GABATCH groups SKUs (Stock Keeping Units) of different orders into multiple lots according to trolley load restrictions so as to reduce the Number of Picking Travels (NPT). It also defines a picking sequence by means of priority lots to avoid Tardiness in Customer Orders (TCO). GATSP maps out the routes of lots inside the WA in order to prevent damages to fragile SKUs and to minimize Total Route Distance (TRD) as well as Total Picking Time (TPT). It was evidenced that, for problems of higher complexity, lots are more homogeneous where the Standard Deviation is small and the Coefficient of Variation (CV) ranges from 11.22% to 25.20% to the TRD. For actual environments where time windows and processing logs are used for off-line lots, the IA-OSB/GA-OPS integration provides optimal time solutions and satisfactory quality to OSB/OPS. In short, this research has gone beyond existing approaches to fill a gap in the literature and provide an important contribution to the practice of optimal OSB/OPS. It can be concluded that the integration of IA-OSB/GA-OPS can maximize billing and improve productivity in order to minimize picking operational time and costs in a WA.

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International Telemetering Conference Proceedings / October 17-20, 1994 / Town & Country Hotel and Conference Center, San Diego, California / The Aircraft Research and Development Unit (ARDU) of the Royal Australian Air Force (RAAF) is the only agency in Australia that performs the full spectrum of military flight testing and is the new custodian of the instrumented weapons range at Woomera. Receiving early attention will be the upgrade and integration of ARDU's telemetry systems with the meteorological and tracking data acquisition capabilities at Woomera to minimize overhead and data turnaround time. To achieve these goals, maximum modularity, extensibility, and product interoperability is being sought in the proposed architecture of all the systems that will need to cooperate on the forecast test programmes. These goals are also driven by the need to be responsive to a wide variety of tasks which presently include structural flight testing of fighter and training aircraft, weapons systems performance evaluation on a variety of combatant aircraft, and a host of other tasks associated with all fixed and rotary wing aircraft in the Army and Air Force inventory. Of all these tasks however, ARDU sees that responsiveness to future testing of F-111Cs fitted with unique Digital Flight Control Systems along with USAF standard F-111Gs may place the most significant demands on data handling —particularly in regard to providing an avionics bus diagnostic capability when performing Operational Flight Programme (OFP) changes to the mission computers. With the timely assistance and advice of Loral Test & Information Systems, who has long-term experience in supporting USAF F-111 test programmes, ARDU is confident of making wise design decisions that will provide the desired flexibility and, at the same time, minimize life-cycle costs by ensuring compliance with the appropriate telemetry and open systems standards. As well, via cooperative agreements with the USAF, the potential exists to acquire proven software products without needing to fund the development costs already absorbed by the USAF. This paper presents ARDU's perception of future needs, a view by LTIS of how best to meet those needs, and, based on ARDU data, a view of how LTIS' proposal will satisfy the requirement to provide maximum extensibility with minimum life-cycle costs.

<p>Due to increased complexity of today’s computer systems, which are manufactured in recent semiconductor technologies, and the fact that recent semiconductor technologies are more liable to soft errors (non-permanent errors) it is inherently difficult to ensure that the systems are and will remain error-free. Depending on the application, a soft error can have serious consequences for the system. It is therefore important to detect the presence of soft errors as early as possible and recover from the erroneous state and maintain correct operation. There is an entire research area devoted on proposing, implementing and analyzing techniques that can detect and recover from these errors, known as fault tolerance. The drawback of using faulttolerance is that it usually introduces some overhead. This overhead may be for instance redundant hardware, which increases the cost of the system, or it may be a time overhead that negatively impacts on system performance. Thus a main concern when applying fault tolerance is to minimize the imposed overhead while the system is still able to deliver the correct error-free operation. In this thesis we have analyzed one well known fault tolerant technique, Rollback-Recovery with Checkpointing (RRC). This technique is able to detect and recover from errors by taking and storing checkpoints during the execution of a job.Therefore we can think as if a job is divided into a number of execution segments and a checkpoint is taken after executing each execution segment. This technique requires the job to be concurrently executed on two processors. At each checkpoint, both processors exchange data, which contains enough information for the job’s state. The exchanged data are then compared. If the data differ, it means that an error is detected in the previous execution segment and it is therefore re-executed. If the exchanged data are the same, it means that no errors are detected and the data are stored as a safe point from which the job can be restarted later. A time overhead due to exchanging data between processors is therefore introduced, and it increases the average execution time of a job, i.e. the average time required for a given job to complete. The overhead depends on the number of links that has to be traversed (due to data exchange) after each execution segment and the number of execution segments that are needed for the given job. The number of links that has to be traversed after each execution segment is twice the distance between the processors that are executing the same job concurrently. However, this is only true if all the links are fully functional. A link failure can result in a longer route for communication between the processors. Even though all links arefully functional, the number of execution segments still depends on error-free probabilities of the processors, and these error-free probabilities can vary between processors. This implies that the choice of processors affects the total number of links the communication has to traverse. Choosing two processors with higher error-free probability further away from eachother increases the distance, but decreases the number of execution segments, which can result in a lower overhead. By carefully determining the mapping for a given job, one can decrease the overhead, hence decreasing the average execution time. Since it is very common to have a larger number of jobs than available resources, it is not only important to find a good mapping to decrease the average execution time for a whole system, but also a good order of execution for a given set jobs (scheduling of the jobs). We propose in this thesis several mapping and scheduling algorithms that aim to reduce the average execution time in a fault-tolerant multiprocessor System-on-Chip, which uses Network-on-Chip as an underlying interconnect architecture, so that the fault-tolerant technique (RRC) can perform efficiently.</p>

Detta arbete syftar till att fördjupa kunskapen om hur violin- och violalärare kan arbeta för att ge sina elever som utövar klassik musik möjlighet att minimera stress och nervositet i samband med provspelning och konserttillfälle. I bakgrundskapitlet presenteras orsaker till samt förebyggande åtgärder för att hantera stress. Dessutom redogörs för musikdidaktiska perspektiv på instrumentalundervisning. Studien har genomförts med kvalitativ intervju som metod. Fyra lärare och musiker har intervjuats. Resultatet i studien styrker tidigare forskning då flera teman är likartade. Dock framkommer nya infallsvinklar på orsaker till stress i resultatet. En av de mer avgörande anledningarna till studenters ökade stressfaktor tydliggörs som avsaknad av mental och praktisk förberedelse. Elevens brist på att se inlärning i en långsiktig process med en utvecklingskurva som inte alltid går parallellt med förväntningarna är en annan orsak som enligt resultatet kan leda till ökad stress. I den förebyggande stresshanteringen betonas vikten av den praktiska förberedelsen som innefattande tekniskt hantverk, övningsmetodik samt att öva på konsertvana inom ramen för gemensam lektion. Vikten av att vara mentalt förberedd för situationen understryks ha betydelse i den förebyggande stresshanteringen. / The purpose of this study is to develop an understanding in how violin teachers can work to provide their students the opportunity to minimize stress and anxiety related to auditions and concerts. In the previous research presented in the background, clear causes and preventive measures to deal with and prevent stress are described. The quantitative interview was the method of the study. Four musicians and teachers were interviewed. The previous research is confirmed by the result that is described in themes by the informants. However, new perspectives on the causes of stress are outlined in the result. One of the more important reasons for an increased stress factor in students is clarified as the absence of mental and practical preparation. A lack in regarding learning as a long term process on behalf of the students, which does not always run parallel with expectations, may lead to increased stress. The importance of the practical preparation includes technical craftsmanship, practice methods, and to practice the concert experience. The importance of being mentally prepared for the situation is a preventive action against stress. The mental preparation before the concert situation, can include relatively simple things like knowing how the room looks like, and that the student has created an image of the audience. Practice in entering the stage, in addition to a presentation approach, are also important factors in reducing stress.

One of the objectives of disaggregation in hierarchical production planning is to minimize the setup costs incurred when changing production from one family to another. In this research, the setup costs are reduced by determining a production schedule that minimizes the number of setups during the planning horizon. Previous solutions to the disaggregation problem have considered discrete-time, and more recently continuous-time formulations. This research extends the continuous time disaggregation approach by incorporating production schedules allowing backorder. A mathematical formulation and a solution algorithm are presented and the computational complexity and convergence properties of the algorithm are discussed. Experimental results, using both deterministic and stochastic demand patterns, which demonstrate the efficacies of the solution approach are provided.