Over the last decade, the semiconductor industry has witnessed a steady increase in its complexity based on improvements in manufacturing processes and equipment. Progress in the technology used is no longer the key to success, however. In fact, the semiconductor technology has reached such a high level of complexity that improvements appear at a slow pace. Moreover, the diffusion of technology among competitors shows that traditional approaches based on technological advances and innovations are not sufficient to remain competitive. A recent crisis in the semiconductor field in the summer 2001 made it even clearer that optimizing the operational control of semiconductor wafer fabrication facilities is a vital key to success. Operating research-oriented studies have been carried out to this end for the last 5 years. None of them, however, suggest a comprehensive model and solution to the operational control problem of a semiconductor manufacturing facility. Two main approaches, namely mathematical programming and dispatching rules, have been explored in the literature so far, either partially or entirely dealing with this problem. Adapting the Shifting Bottleneck (SB) procedure is a third approach that has motivated many studies. Most research focuses on optimizing a certain objective function under idealized conditions and thus does not take into consideration system disruptions such as machine breakdown. While many papers address the adaptations of the SB procedure, the problem of re-scheduling jobs dynamically to take disruptions and local disturbances (machines breakdown, maintenance...) into consideration shows interesting perspectives for research. Dealing with local disturbances in a production environment and analyzing their impact on scheduling policies is a complex issue. It becomes even more complex in the semiconductor industry because of the numerous inherent constraints to take into account. The problem that is addressed in this thesis consists of studying dynamic scheduling in a job-shop environment where local disturbances occur. This research focuses on scheduling a large job shop and developing re-scheduling policies when local disturbances occur. The re-scheduling can be applied to the whole production horizon considered in the instance, or applied to a restricted period T that becomes a decision variable of the problem. The length of the restricted horizon T of re-scheduling can influence significantly the overall results. Its impact on the general performance is studied. Future extensions can be made to include constraints that arise in the semiconductors industry, such as the presence of parallel and batching machines, reentrant flows and the lot dedication problem. The theoretical results developed through this research will be applied to data sets to study their efficiency. We hope this methodology will bring useful insights to dealing effectively with local disturbances in production environments. / Master of Science

Especialmente nas últimas quatro décadas, muitos estudos se voltaram às variáveis determinantes para a implementação efetiva de sistemas flexíveis de manufatura, tais como seu design, sequenciamento e controle. Neste ínterim, o manejo apropriado do conjunto de ferramentas necessárias para a fabricação de um respectivo lote de produtos foi destacado como fator crucial no desempenho do sistema de produção como um todo. Neste trabalho, abordamos a otimização do número de inserções e remoções de ferramentas no magazine de uma ou mais máquinas numericamente controladas, admitindo-se que uma parcela significativa do tempo de produção é dispensada com estas trocas de ferramentas. De forma mais precisa, a minimização do número de trocas de ferramentas consiste em determinar a ordem de processamento de um conjunto de tarefas, bem como o carregamento ótimo do(s) compartimento(s) de ferramentas da(s) máquina(s), a fim de que o número de trocas seja minimizado. Como demostrado na literatura, mesmo o caso restrito à existência de apenas uma máquina de manufatura (MTSP, do inglês Minimization of Tool Switches Problem) é um problema NP-difícil, o que pode justificar o fato observado de que a maioria dos métodos de solução existentes o abordam de maneira heurística. Consequentemente, concluímos que a extensão ao contexto de múltiplas máquinas é também um problema NP-difícil, intrinsecamente complicado de se resolver. Nosso objetivo consiste em estudar formas eficientes de otimizar o número de trocas de ferramentas em ambientes equipados com máquinas flexíveis de manufatura. Para tanto, abordamos o problema básico, MTSP, e duas de suas variantes, em níveis crescentes de abrangência, que consideram o sequenciamento de tarefas em um conjunto de: (i) máquinas paralelas e idênticas (IPMTC, do inglês Identical Parallel Machines problem with Tooling Constraints); e (ii) máquinas paralelas e idênticas inseridas em um ambiente do tipo job shop (JSSPTC, do inglês Job Shop Scheduling Problem with Tooling Constraints). Classificamos as principais contribuições desta tese com respeito a três aspectos. Primeiramente, empurramos as fronteiras da literatura do MTSP propondo formulações matemáticas para os problemas IPMTC e JSSPTC. Desenvolvemos, também, algoritmos baseados em diferentes técnicas de resolução, como redução de domínio, Path relinking, Adaptive large neighborhood search e a elaboração de regras de despacho. Por último, com o intuito de bem avaliar a eficiência e o alcance de nossos métodos, propomos três novos conjuntos de instâncias teste. Acreditamos, assim, que este trabalho contribui positivamente com pesquisas futuras em um cenário abrangente dentro da minimização das trocas de ferramentas em um sistema flexível de manufatura. / Several studies, especially in the last four decades, have focused on decisive elements for the effective implementation of flexible manufacturing systems, such as their design, scheduling and control. In the meantime, the appropriate management of the set of tools needed to manufacture a certain lot of products has been highlighted as a crucial factor in the performance of the production system as a whole. This work deals with the optimization of the number of insertions and removals from the magazine of one or more numerical controlled machines, assuming that a significant part of the production time is wasted with such tool switches. More precisely, the minimization of tool switches problem (MTSP) consists on determining the processing order of a set of jobs, as well as the optimal loading of the magazine(s) of the machine(s), so that the total number of switches is minimized. As formally demonstrated in the literature, the MTSP is a NP-hard problem even when considering the existence of only one manufacturing machine, which could justify the fact that most of the solution methods tackles it heuristically. We thus conclude that its extension to the case of multiples machines is also NP-hard and, therefore, a problem intrinsically difficult to solve. Our goal consists in studying efficient ways to optimize the number of tool switches in environments equipped with flexible manufacturing machines. For that, we address the basic problem, MTSP, and two MTSP variants, in increasing levels of reach, that consider the job sequencing in a set of: (i) identical parallel machines (Identical Parallel Machines problem with Tooling Constraints, IPMTC); and (ii) identical parallel machines inserted in a job shop environment (Job Shop Scheduling Problem with Tooling Constraints, JSSPTC). The main contributions of this thesis are classified according three aspects. First, we pushed the frontier of the MTSP literature by proposing mathematical formulations for IPMTC and JSSPTC. We also developed algorithms based on different solution techniques, such as domain reduction, Path Relinking, Adaptive Large Neighborhood Search and dispatching rules. Finally, to fully evaluate the effectiveness and limits of our methods, three new sets of benchmark instances were generated. We believe that this work contributes positively to the future of research in a broad scenario inside the minimization of tool switches in flexible manufacturing systems.

Nous présentons les enjeux du management environnemental et soulignons l’importance d’une politique d’économie d’énergie pour les entreprises. Nous proposons un modèle pour déterminer le bilan énergétique de la fabrication en intégrant les différentes phases productives et non-productives. Nous définissons un double objectif pour la minimisation de la durée de production et de la consommation d’énergie. Nous appliquons ce modèle à l’ordonnancement d’ateliers job-shop flexibles. Pour déterminer la solution optimale nous utilisons deux classes de méthodes : - La première relève des algorithmes génétiques. Nous proposons différents types d’algorithmes pour résoudre ce problème multicritère. Nous proposons par exemple de faire évoluer deux populations pour minimiser respectivement l’énergie consommée et la durée de production et de les croiser pour atteindre l’objectif global. - La seconde relève de la programmation sous contrainte. Nous proposons de rechercher la solution optimale en développant une double arborescence pour évaluer l’énergie consommée et la durée de production. Nous construisons notre algorithme en partant des tâches à réaliser sur les machines ou en partant des machines qui réaliseront les tâches. Nous discutons de la construction du front de Pareto pour l’obtention de la meilleure solution.Nous terminons en comparant les différentes approches et en discutant leur pertinence pour traiter des problèmes de différentes tailles. Nous proposons également plusieurs améliorations et quelques pistes pour de futures recherches. / We present the challenges of environmental management and underline the importance of an energy saving policy for companies. We propose a model to determine the energy balance of manufacturing by integrating the different productive and non-productive phases. We define two purposes for minimizing production time and energy consumption. We apply this model to the scheduling of flexible job-shop workshops. To determine the optimal solution we use two types of methods: - The first is genetic algorithms. We propose different types of algorithms to solve this multi-criteria problem. For example, we propose to develop two populations to minimize the energy consumed and the production time, and to cross them to achieve the overall objective. - The second is constraint programming. We propose to find the optimal solution by developing a double tree to evaluate the energy consumed and the production time. We build our algorithm starting from the tasks to be performed on the machines or from the machines that will perform the tasks. We discuss the construction of the Pareto front to get the best solution.We finish by comparing the different approaches and discussing their relevance to deal with problems of different sizes. We also offer several improvements and some leads for future research.

Made available in DSpace on 2016-12-23T14:33:37Z (GMT). No. of bitstreams: 1 dissertacao.pdf: 1052399 bytes, checksum: b17ce224ca3822e277c997fd00bd2c67 (MD5) Previous issue date: 2006-11-29 / Este trabalho apresenta um Sistema Imune Artificial (SIA) para tratar problemas de escalonamento. O Sistema Imunológico Artificial desenvolvido neste projeto baseia-se na estrutura arquitetura e funcionamento dos Sistemas Imunes Biológicos ou Naturais. O uso de Algoritmo Genético (AG) fez-se necessário para gerar os indivíduos a serem escalonados, representando os antígenos e anticorpos do SIA. Cada indivíduo gerado pelo AG representa um conjunto de tarefas processadas em um conjunto de máquinas. Os indivíduos são avaliados por uma função de aptidão que representa o processo de seleção natural. A evolução dos indivíduos e consequentemente das populações são obtidas aplicando-se os operadores genéticos de crossover e mutação. As tarefas e as máquinas, utilizadas para o escalonamento, representa o problema de Job Shop Scheduling (JSS). Ao problema, foram aplicados alguns testes clássicos da literatura, onde se verificou a viabilidade dos SIA para tratamento de problemas de escalonamento. Ainda com os testes, pode-se observar o comportamento do sistema durante toda a execução, possibilitando assim, uma análise criteriosa das funcionalidades do sistema e dos resultados gerados pela massa de teste, observados durante um período de tempo. A representação dos sistemas imunológicos naturais através de algoritmos computacionais tem inspirado pesquisadores de todo o mundo, a motivação é que os sistemas imunológicos possuem características de paralelismo adaptabilidade e aprendizagem, além da possibilidade de serem aplicados em diversos problemas das mais diversas áreas, devido sua portabilid ade. / This work presents an Artificial Immune System (AIS) to deal with problems scheduling. The Artificial Immunologic System developed in this project was based on the structure, architecture and functioning of the Biological or Natural Immune Systems. The use of Genetic Algorithm (GA) became necessary to represent the antibodies and antigens of the AIS. Each individual generated for the GA represented a processed task set library in a set of machines. The evaluation of each individual was given by a fitness function that represents the process of natural selection. The evolution of the individuals, and population as a consequence was obtained by applying the genetic operators of crossover e mutation. The machines and the tasks used for the scheduling represent the problem of Job Shop Scheduling (JSS). Some classic tests of the literature where applied to the problem in order to verify the viability of the AIS on the treatment of task of scheduling problems. Those tests also demonstrated the system s behavior its entire execution, therefore, allowing for a detailed analysis of the system s functionalities sets for certain time period. The representation of the natural immunologic systems through computational algorithms inspires from all over world researchers. The motivation is that the immunologic systems possess parallelism characteristics adaptability and learning, which can be applied in several problems found in many areas, had its portability.

Nos travaux concernent l’étude d’une extension d’un problème d’ordonnancement bien connu sous l’appellation job shop. Nous appelons cette extension le General Flexible Job Shop Scheduling Problem (GFJSSP). Celui-ci se rencontre dans différents types d’ateliers ayant comme caractéristique commune d’être soumis à des contraintes dues à des ressources de transport. Le GFJSSP se caractérise par l’intégration de machines et robots flexibles. Le terme General induit par ailleurs la présence de robots dont la capacité est supposée unitaire dans notre étude, des temps opératoires bornés, et la possibilité de prise en compte d’emplacements de stockage spécifiques. Après avoir défini l’atelier et le problème correspondant à cette extension, nous avons proposé deux modélisations du GFJSSP ainsi défini : une première modélisation mathématique linéaire, et une modélisation graphique, qui correspond à une généralisation du graphe disjonctif couramment utilisé pour les problèmes de job shop. Nous avons ensuite abordé la résolution suivant deux étapes : tout d’abord en nous focalisant sur l’aspect séquencement des tâches de traitement et de transport, pour lequel nous avons élaboré deux méthodes heuristiques (de type Tabou et basée sur une procédure de shifting bottleneck améliorée) ; puis en intégrant dans un deuxième temps la problématique de l’affectation induite par la flexibilité de certaines ressources. Pour cette dernière étape, nous avons combiné les méthodes précédentes avec un algorithme génétique. L’algorithme hybride obtenu nous permet de résoudre des instances de la littérature correspondant à divers cas spécifiques, avec des résultats assez proches des meilleures méthodes dédiées. A termes, il pourrait être intégré dans un système d'aide à la décision général qui s’affranchirait de la phase d’identification préalable du type de job shop considéré, et serait adapté à la résolution de nombreux cas (avec ou sans problème d'affectation, temps de traitement fixes ou bornés, avec ou sans stockage, etc..). / Our work focuses on an extension of the well known job shop scheduling problem. We call this extension the General Flexible Job Shop Scheduling Problem (GFJSSP). It occurs in various kinds of workshops which are particularly constrained by one or several transportation resources (called robots). GFJSSP is characterized by the flexibility of both machines and robots. In the studied problem, the term General involves unitary capacity transportation resources, bounded processing times, and possible input/output buffers for machines. After defining the workshop and the corresponding problem, we proposed two kinds of model for the GFJSSP: a mathematical model, and a graphical one. This last one is a generalization of the disjunctive graph commonly used for job shop problems. We then addressed the resolution in two steps: firstly, by focusing on the sequencing of processing and transportation tasks. For this purpose we have developed two heuristics (Tabu search and an improved shifting bottleneck procedure). Secondly, we have considered the assignment problem involved by the flexibility of some resources. For this last step, we combined the above methods with a genetic algorithm. This hybrid algorithm allowed us to solve various specific cases of instances in the literature, with performance rather close to the best dedicated methods. In the future, it could be integrated within a general decision support system which could emancipate from the initial identification phase of the considered type of job shop, and which would be suitable for solving many cases (with or without assignment problem, fixed or bounded processing times, with or without storage, and so on).

Le management de la chaîne logistique concerne un large éventail d’activités. Nombreuses ceux qui ont un caractère incertain apportant souvent des conséquences inattendues. Malgré cela, l’incertitude est fréquemment non considérée dans la gestion de la chaîne logistique traditionnelle. En plus de l’incertitude, l’indisponibilité des ressources augmentera la complexité du problème. En prenons en compte les contraintes d’incertitude et de disponibilité nous étudions le management de la chaîne logistique selon différents aspects. Cette thèse représente une tentative de recherche afin d’aborder ce problème d’une façon systématique et complète et nous espérons que notre travail contribuera aux futurs travaux de recherche et sera utile aux gestionnaires de la chaîne logistique. Nous nous concentrons sur trois sources classiques de l’incertitude ; celle de la demande, celle la fabrication et celle liée à la distribution. Pour chaque source d’incertitude, nous analysons ses causes et ses impacts sur les performances de la chaîne logistique. L’incertitude est spécifiée dans des problèmes classiques concrets et des approches sont proposées pour les résoudre. Nous nous sommes également focalisés sur le problème bi-niveau de vendeur de journaux qui représente une chaîne logistique miniature, concerné par une double incertitude. Les méthodes utilisées offrent une bonne démonstration du traitement des variables incertaines dans les problèmes de décision / Supply chain management involves a wide range of activities. Among most of them, uncertainty exists inherently and always brings some consequence not expected. However, uncertainty is not considered much in conventional supply chain management. In the case where availability of resources is not what we expect, complexity of supply chain management increases. Taking constraints of uncertainty and availability into account, we aim to discuss supply chain management from different aspects. This thesis is an attempt of systematic and complete research from this point and we would like to offer some references to researchers and managers in supply chain. We focus on three classic sources of uncertainty: demand, manufacturing and distribution. For each source of uncertainty, we analyze its cause and its impact to the performance of the supply chain. Uncertainty is specified into concrete classic problem and an approach is proposed to solve it. Furthermore, bi-level newsboy problem as a miniature of supply chain, is focused under double uncertain environment. Treating uncertain variables is actually a treatment on operational level. The methods used offer good demonstration in treating uncertain variables in decision problems

Made available in DSpace on 2016-06-02T19:51:35Z (GMT). No. of bitstreams: 1 1770.pdf: 2888839 bytes, checksum: 18c57ba21e9192d597b74f8d1d0fc997 (MD5) Previous issue date: 2008-02-29 / Universidade Federal de Minas Gerais / This is a study of approximations based on parametric decomposition methods used in open queueing networks for modeling discrete job-shop manufacturing systems. These approximations play an important role in evaluating the performance of productive systems and have proved effective in many situations. Besides, these approximations are relatively easy to apply requiring fewer data compared to other methods because they use the average rate and SCV (square coefficient of variation) as the only parameters to characterize the network arrival and service processes. This work is aimed at analyzing and comparing several approximations since they are not yet available in the literature. Hence, several network situations were tested in order to identify the most adequate approximation for each situation. Firstly, a two-station network was analyzed followed by the analysis of a five-station network and lastly, a real example of a semiconductor plant, analyzed by Bitran e Tirupati (1988), was used. In order to reach these goals, the state of the art of approximation methods to evaluate the performance of open queueing networks was studied, and the approximations were compared using the experiment planning technique, important factors for building network configuration and data analysis The findings of this work demonstrate that approximations can be highly efficient to evaluate the performance of discrete job-shop manufacturing systems. Regardless of the configurations studied, it is worth mentioning that approximations 3 and 2, in general, showed the best results if compared to the other values obtained from simulations to evaluate the performance of open queueing networks, OQN,. The other approximations tended to overestimate E(Lj) when the number of stations is higher. This study intends to contribute to the development of computing systems in order to support project decisions and the planning and control of discrete manufacturing systems using approximations based on the parametric decomposition method / Esta dissertação estuda as aproximações baseadas nos métodos analíticos paramétricos de decomposição usados em redes de filas abertas que modelam sistemas discretos de manufatura do tipo job-shop. Estas aproximações possuem um importante papel na avaliação do desempenho de sistemas produtivos e vem se mostrando eficiente para uma grande diversidade de situações. Além disso, são aproximações relativamente fáceis de serem aplicadas, necessitando poucos dados em relação a outros métodos, pois utilizam apenas a média e o scv (coeficiente quadrático de variação) como parâmetros para caracterizar os processos de chegadas e os processos de serviço da rede. O foco deste trabalho está em realizar análises e comparações entre diversas aproximações, pois ainda não existe nenhuma comparação mais efetiva entre elas na literatura. Para isso, diversas situações de redes foram exploradas para identificar quais aproximações são mais adequadas para quais situações. Primeiramente é analisado uma rede com 2 estações, posteriormente uma outra com 5 estações e por fim usou um exemplo real de uma fábrica de semi-condutores, analisada por Bitran e Tirupati (1988). Para que seja possível atingir esses objetivos, estudou-se o estado da arte das aproximações dos métodos de avaliação de desempenho para redes de filas abertas, e comparouse as aproximações por meio de técnicas de planejamento de experimentos, parte importante na construção das configurações das redes e análise dos resultados. Os resultados apresentados nesta dissertação mostram que essas aproximações podem ser bem eficientes ao avaliar o desempenho de sistemas discretos de manufatura do tipo job-shop. Independente das configurações analisadas, vale destacar a Aproximação 3 e a Aproximação 2, em geral, obtendo os melhores resultados, entre as aproximações, em comparação aos valores obtidos pela simulação para avaliar o desempenho de redes de filas OQN. As outras aproximações demonstraram certo comportamento em sobreestimar E(Lj), quando o número de estações aumentam. Este estudo pretende contribuir para o desenvolvimento de sistemas computacionais 13 para apoiar decisões de projeto, planejamento e controle dos sistemas discretos de manufatura, usando aproximações baseadas em métodos de decomposição paramétrico

Especialmente nas últimas quatro décadas, muitos estudos se voltaram às variáveis determinantes para a implementação efetiva de sistemas flexíveis de manufatura, tais como seu design, sequenciamento e controle. Neste ínterim, o manejo apropriado do conjunto de ferramentas necessárias para a fabricação de um respectivo lote de produtos foi destacado como fator crucial no desempenho do sistema de produção como um todo. Neste trabalho, abordamos a otimização do número de inserções e remoções de ferramentas no magazine de uma ou mais máquinas numericamente controladas, admitindo-se que uma parcela significativa do tempo de produção é dispensada com estas trocas de ferramentas. De forma mais precisa, a minimização do número de trocas de ferramentas consiste em determinar a ordem de processamento de um conjunto de tarefas, bem como o carregamento ótimo do(s) compartimento(s) de ferramentas da(s) máquina(s), a fim de que o número de trocas seja minimizado. Como demostrado na literatura, mesmo o caso restrito à existência de apenas uma máquina de manufatura (MTSP, do inglês Minimization of Tool Switches Problem) é um problema NP-difícil, o que pode justificar o fato observado de que a maioria dos métodos de solução existentes o abordam de maneira heurística. Consequentemente, concluímos que a extensão ao contexto de múltiplas máquinas é também um problema NP-difícil, intrinsecamente complicado de se resolver. Nosso objetivo consiste em estudar formas eficientes de otimizar o número de trocas de ferramentas em ambientes equipados com máquinas flexíveis de manufatura. Para tanto, abordamos o problema básico, MTSP, e duas de suas variantes, em níveis crescentes de abrangência, que consideram o sequenciamento de tarefas em um conjunto de: (i) máquinas paralelas e idênticas (IPMTC, do inglês Identical Parallel Machines problem with Tooling Constraints); e (ii) máquinas paralelas e idênticas inseridas em um ambiente do tipo job shop (JSSPTC, do inglês Job Shop Scheduling Problem with Tooling Constraints). Classificamos as principais contribuições desta tese com respeito a três aspectos. Primeiramente, empurramos as fronteiras da literatura do MTSP propondo formulações matemáticas para os problemas IPMTC e JSSPTC. Desenvolvemos, também, algoritmos baseados em diferentes técnicas de resolução, como redução de domínio, Path relinking, Adaptive large neighborhood search e a elaboração de regras de despacho. Por último, com o intuito de bem avaliar a eficiência e o alcance de nossos métodos, propomos três novos conjuntos de instâncias teste. Acreditamos, assim, que este trabalho contribui positivamente com pesquisas futuras em um cenário abrangente dentro da minimização das trocas de ferramentas em um sistema flexível de manufatura. / Several studies, especially in the last four decades, have focused on decisive elements for the effective implementation of flexible manufacturing systems, such as their design, scheduling and control. In the meantime, the appropriate management of the set of tools needed to manufacture a certain lot of products has been highlighted as a crucial factor in the performance of the production system as a whole. This work deals with the optimization of the number of insertions and removals from the magazine of one or more numerical controlled machines, assuming that a significant part of the production time is wasted with such tool switches. More precisely, the minimization of tool switches problem (MTSP) consists on determining the processing order of a set of jobs, as well as the optimal loading of the magazine(s) of the machine(s), so that the total number of switches is minimized. As formally demonstrated in the literature, the MTSP is a NP-hard problem even when considering the existence of only one manufacturing machine, which could justify the fact that most of the solution methods tackles it heuristically. We thus conclude that its extension to the case of multiples machines is also NP-hard and, therefore, a problem intrinsically difficult to solve. Our goal consists in studying efficient ways to optimize the number of tool switches in environments equipped with flexible manufacturing machines. For that, we address the basic problem, MTSP, and two MTSP variants, in increasing levels of reach, that consider the job sequencing in a set of: (i) identical parallel machines (Identical Parallel Machines problem with Tooling Constraints, IPMTC); and (ii) identical parallel machines inserted in a job shop environment (Job Shop Scheduling Problem with Tooling Constraints, JSSPTC). The main contributions of this thesis are classified according three aspects. First, we pushed the frontier of the MTSP literature by proposing mathematical formulations for IPMTC and JSSPTC. We also developed algorithms based on different solution techniques, such as domain reduction, Path Relinking, Adaptive Large Neighborhood Search and dispatching rules. Finally, to fully evaluate the effectiveness and limits of our methods, three new sets of benchmark instances were generated. We believe that this work contributes positively to the future of research in a broad scenario inside the minimization of tool switches in flexible manufacturing systems.

[EN] Many industrial problems can be modelled as a scheduling problem where some resources are assigned to tasks so as to minimize the completion time, to reduce the use of resources, idle time, etc. There are several scheduling problems which try to represent different kind of situations that can appear in real world problems. Job Shop Scheduling Problem (JSP) is the most used problem. In JSP there are different jobs, every job has different tasks and these tasks have to be executed by different machines. JSP can be extended to other problems in order to simulate more real problems. In this work we have used the problem job shop with operators JSO(n,p) where each task must also be assisted by one operator from a limited set of them. Additionally, we have extended the classical JSP to a job-shop scheduling problem where machines can consume different amounts of energy to process tasks at different rates (JSMS). In JSMS operation has to be executed by a machine that has the possibility to work at different speeds. Scheduling problems consider optimization indicators such as processing time, quality and cost. However, governments and companies are also interested in energy-consumption due to the rising demand and price of fuel, the reduction in energy commodity reserves and growing concern about global warming. In this thesis, we have developed new metaheuristic search techniques to model and solve the JSMS problem. Robustness is a common feature in real life problems. A system persists if it remains running and maintains his main features despite continuous perturbations, changes or incidences. We have developed a technique to solve the $JSO(n,p)$ problem with the aim of obtaining optimized and robust solutions. We have developed a dual model to relate optimality criteria with energy consumption and robustness/stability in the JSMS problem. This model is committed to protect dynamic tasks against further incidences in order to obtain robust and energy-aware solutions. The proposed dual model has been evaluated with a memetic algorithm to compare the behaviour against the original model. In the JSMS problem there are a relationship between Energy-efficiency, Robustness and Makespan. Therefore, the relationship between these three objectives is studied. Analytical formulas are proposed to analyse the relationship between these objectives. The results show the trade-off between makespan and robustness, and the direct relationship between robustness and energy-efficiency. To reduce the makespan and to process the tasks faster, energy consumption has to be increased. When the energy consumption is low it is because the machines are not working at highest speed. So, if an incidence appears, the speed of these machines can be increased in order to recover the time lost by the incidence. Hence robustness is directly related with energy consumption. Additionally, robustness is also directly related with makespan because, when makespan increases, there are more gaps in the solution, these incidences can be absorbed by these natural buffers. The combination of robustness and stability gives the proposal an added value due to since an incidence cannot be directly absorbed by the disrupted task and it can be repaired by involving only a small number of tasks. In this work we propose two different techniques to manage rescheduling over the JSMS problem. This work represents a breakthrough in the state of the art of scheduling problems and in particular the problem where energy consumption can be controlled by the rate of the machines. / [ES] Muchos de los problemas industriales se pueden modelar como un problema de scheduling donde algunos recursos son asignados a tareas a fin de minimizar el tiempo de finalización, para reducir el uso de los recursos, el tiempo de inactividad, etc. Job-Shop scheduling (JSP) es el problema más utilizado. En JSP hay diferentes trabajos, cada trabajo tiene diferentes tareas y estas tareas tienen que ser ejecutadas por diferentes máquinas. JSP puede ser extendido a otros problemas con el fin de simular una mayor cantidad de problemas reales. En este trabajo se ha utilizado el problema job shop scheduling con operadores JSO(n, p), donde cada tarea también debe ser asistida por un operador de un conjunto limitado de ellos. Además, hemos ampliado el clásico problema JSP a un problema donde las máquinas pueden consumir diferentes cantidades de energía al procesar tareas a diferentes velocidades (JSMS). En JSMS las operaciones tiene que ser ejecutadas por una máquina que tiene la posibilidad de trabajar a diferentes velocidades. Los problemas de scheduling consideran indicadores de optimización tales como: el procesamiento de tiempo, la calidad y el coste. Sin embargo, hoy en día los gobiernos y los empresarios están interesados también en el control del consumo de energía debido al aumento de la demanda y del precio de los combustibles, la reducción de las reservas de materias primas energéticas y la creciente preocupación por el calentamiento global. En esta tesis, hemos desarrollado nuevas técnicas de búsqueda metaheurística para modelar y resolver el problema JSMS. La robustez es una característica común en los problemas de la vida real. Un sistema persiste si permanece en funcionamiento y mantiene sus principales características a pesar de las perturbaciones continuas, cambios o incidencias. Hemos desarrollado una técnica para resolver el problema JSO(n, p) con el objetivo de obtener soluciones robustas y optimizadas. Hemos desarrollado un modelo dual para relacionar los criterios de optimalidad con el consumo de energía y la robustez/estabilidad en el problema JSMS. Este modelo se ha desarrollado para proteger a las tareas dinámicas contra incidencias, con el fin de obtener soluciones sólidas y que tengan en cuenta el consumo de la energía. El modelo dual propuesto ha sido evaluado con un algoritmo memético para comparar el comportamiento frente al modelo original. En el problema JSMS hay una relación entre la eficiencia energética, la robustez y el makespan. Por lo tanto, se estudia la relación entre estos tres objetivos. Se desarrollan fórmulas analíticas para representar la relación estimada entre estos objetivos. Los resultados muestran el equilibrio entre makespan y robustez, y la relación directa entre la robustez y eficiencia energética. Para reducir el makespan, el consumo de energía tiene que ser aumentado para poder procesar las tareas más rápido. Cuando el consumo de energía es bajo, debido a que las máquinas no están trabajando a la velocidad más alta, si una incidencia aparece, la velocidad de estas máquinas puede ser aumentada con el fin de recuperar el tiempo perdido por la incidencia. Por lo tanto la robustez está directamente relacionada con el consumo de energía. Además, la robustez también está directamente relacionada con el makespan porque, cuando el makespan aumenta hay más huecos en la solución, que en caso de surgir incidencias, estas pueden ser absorbidas por estos buffers naturales. La combinación de robustez y estabilidad da un valor añadido debido a que si una incidencia no puede ser absorbida directamente por la tarea interrumpida, esta puede ser reparada mediante la participación un pequeño número de tareas.En este trabajo se proponen dos técnicas diferentes para gestionar el rescheduling sobre el problema JSMS. Este trabajo representa un avance en el estado del arte en los problemas de scheduling y en el problema donde el consumo de energía p / [CAT] Molts dels problemes industrials es poden modelar com un problema de scheduling on alguns recursos són assignats a tasques a fi de minimitzar el temps de finalització, per a reduir l'ús dels recursos, el temps d'inactivitat, etc. Existeixen diversos tipus de problemes de scheduling que intenten representar diferents situacions que poden aparèixer en els problemes del món real. Job-Shop scheduling (JSP) és el problema més utilitzat. En JSP hi ha diferents treballs, cada treball té diferents tasques i aquestes tasques han de ser executades per diferents màquines. JSP pot ser estès a altres problemes amb la finalitat de simular una major quantitat de problemes reals. En aquest treball s'ha utilitzat el problema job shop scheduling amb operadors JSO(n, p), on cada tasca també ha de ser assistida per un operador d'un conjunt limitat d'ells. A més, hem ampliat el clàssic problema JSP a un problema on les màquines poden consumir diferents quantitats d'energia per a processar tasques a diferents velocitats (JSMS). Els problemes de scheduling consideren indicadors d'optimització tals com: el processament de temps, la qualitat i el cost. No obstant açò, avui en dia els governs i els empresaris estan interessats també amb el control del consum d'energia a causa de l'augment de la demanda i del preu dels combustibles, la reducció de les reserves de matèries primeres energètiques i la creixent preocupació per l'escalfament global. En aquesta tesi, hem desenvolupat noves tècniques de cerca metaheurística per a modelar i resoldre el problema JSMS. La robustesa és una característica comuna en els problemes de la vida real. Un sistema persisteix si continua en funcionament i manté les seues principals característiques malgrat les pertorbacions contínues, canvis o incidències. Hem desenvolupat una tècnica per a resoldre el problema JSO(n, p) amb l'objectiu d'obtenir solucions robustes i optimitzades. Hem desenvolupat un model dual per a relacionar els criteris de optimalidad amb el consum d'energia i la robustesa/estabilitat en el problema JSMS. Aquest model s'ha desenvolupat per a protegir a les tasques dinàmiques contra incidències, amb la finalitat d'obtenir solucions sòlides i que tinguen en compte el consum de l'energia. El model dual proposat ha sigut evaluat amb un algorisme memético per a comparar el comportament front un model original. En el problema JSMS hi ha una relació entre l'eficiència energètica, la robustesa i el makespan. Per tant, s'estudia la relació entre aquests tres objectius. Es desenvolupen fórmules analítiques per a representar la relació estimada entre aquests objectius. Els resultats mostren l'equilibri entre makespan i robustesa, i la relació directa entre la robustesa i l'eficiència energètica. Per a reduir el makespan, el consum d'energia ha de ser augmentat per a poder processar les tasques més ràpid. Quan el consum d'energia és baix, a causa que les màquines no estan treballant a la velocitat més alta, si una incidència apareix, la velocitat d'aquestes màquines pot ser augmentada amb la finalitat de recuperar el temps perdut per la incidència. Per tant la robustesa està directament relacionada amb el consum d'energia. A més, la robustesa també està directament relacionada amb el makespan perquè, quan el makespan augmenta hi ha més buits en la solució, que en cas de sorgir incidències, aquestes poden ser absorbides per els buffers naturals. La combinació de robustesa i estabilitat dóna un valor afegit a causa de que si una incidència no pot ser absorbida directament per la tasca interrompuda, aquesta pot ser reparada mitjançant la participació d'un xicotet nombre de tasques. En aquest treball es proposen dues tècniques diferents per a gestionar el rescheduling sobre el problema JSMS. Aquest treball representa un avanç en l'estat de l'art en els problemes de scheduling i, en particular, en el problema on el consum d'energia pot ser controlat per / Escamilla Fuster, J. (2016). Eficiencia Energética y Robustez en Problemas de Scheduling [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/64062 / TESIS

So far the optimization of integration processes between heterogeneous data sources is still an open challenge. A first step towards sufficient techniques was the specification of a universal benchmark for integration systems. This DIPBench allows to compare solutions under controlled conditions and would help generate interest in this research area. However, we see the requirement for providing a sophisticated toolsuite in order to minimize the effort for benchmark execution. This demo illustrates the use of the DIPBench toolsuite. We show the macro-architecture as well as the micro-architecture of each tool. Furthermore, we also present the first reference benchmark implementation using a federated DBMS. Thereby, we discuss the impact of the defined benchmark scale factors. Finally, we want to give guidance on how to benchmark other integration systems and how to extend the toolsuite with new distribution functions or other functionalities.