The demand for devices like Personal Digital Assistants (PDA’s), Laptops, Smart Mobile Phones, are at an all time high. As the demand for these devices increases, so is the push to provide sophisticated functionalities in these devices. However energy consumption has become a major constraint in providing increased functionality for these devices. A majority of the applications meant for these devices are rich with multimedia content. In this thesis, we propose two approaches for compiler directed energy reduction, one targeting the memory subsystem and another the processor. The first technique is a compiler directed optimization technique that reduces the energy consumption of the memory subsystem, for an off-chip partitioned memory archi- tecture, having multiple memory banks, and various low-power operating modes for each of these banks. We propose an efficient layout of the data segment to reduce the number of simultaneously active memory banks, so that the other memory banks that are inactive can be put to low power modes to reduce the energy. We model this problem as a graph partitioning problem, and use well known heuristics to solve the same. We also propose a simple Integer Linear Programming (ILP) formulation for the above problem. Perfor- mance results indicate that our approach achieves an energy reduction of 20% compared to the base scheme, and a reduction of 8%-10% over a previously suggested method. Also, our results are well within the optimal results obtained by using ILP method. The second approach proposed in this thesis reduces the dynamic energy consumed by the processor using dynamic voltage and frequency scaling technique. Earlier works on dynamic voltage scaling focused mainly on performing voltage scaling when the CPU is waiting for memory subsystem or concentrated chiefly on loop nests and/or subroutine calls having sufficient number of dynamic instructions. We concentrate on coarser pro- gram regions and for the first time uses program phase behavior for performing dynamic voltage scaling. We relate the Dynamic Voltage Scaling Problem to the Multiple Choice Knapsack Problem, and use well known heuristics to solve it efficiently. Also, we develop a simple Integer Linear Programming (ILP) problem formulation for this problem. Experi-mental evaluation on a set of media applications reveal that our heuristic method obtains 35-40% reduction in energy consumption on an average, with a negligible performance degradation. Further the energy consumed by our heuristic solution is within 1% the optimal solution obtained by the ILP approach.

Instruction scheduling and Software pipelining are important compilation techniques which reorder instructions in a program to exploit instruction level parallelism. They are essential for enhancing instruction level parallelism in architectures such as very Long Instruction Word and tiled processors. This thesis addresses two important problems in the context of these instruction reordering techniques. The first problem is for general purpose applications and architectures, while the second is for media and graphics applications for tiled and multi-core architectures. The first problem deals with software pipelining which is an instruction scheduling technique that overlaps instructions from multiple iterations. Software pipelining increases the register pressure and hence it may be required to introduce spill instructions. In this thesis, we model the problem of register allocation with optimal spill code generation and scheduling in software pipelined loops as a 0-1 integer linear program. By minimizing the amount of spill code produced, the formulation ensures that the initiation interval (II) between successive iterations of the loop is not increased unnecessarily. Experimental results show that our formulation performs better than the existing heuristics by preventing an increase in the II and also generating less spill code on average among loops extracted from Perfect Club and SPEC benchmarks. The second major contribution of the thesis deals with the code size aware scheduling of stream programs. Large scale synchronous dataflow graphs (SDF’s) and StreamIt have emerged as powerful programming models for high performance streaming applications. In these models, a program is represented as a dataflow graph where each node represents an autonomous filter and the edges represent the channels through which the nodes communicate. In constructing static schedules for programs in these models, it is important to optimize the execution time buffer requirements of the data channel and the space required to store the encoded schedule. Earlier approaches have either given priority to one of the requirements or proposed ad-hoc methods for generating schedules with good trade-offs. In this thesis, we propose a genetic algorithm framework based on non-dominated sorting for generating serial schedules which have good trade-off between code size and buffer requirement. We extend the framework to generate software pipelined schedules for tiled architectures. From our experiments, we observe that the genetic algorithm framework generates schedules with good trade-off and performs better than the earlier approaches.

No description available.

Any unexpected disruption to WDM (Wavelength Division Multiplexing) based optical networks which carry data traffic at tera-bit per second may result in a huge loss to its end-users and the carrier itself. Thus survivability has been well-recognized as one of the most important objectives in the design of optical Internet. This thesis proposes a novel survivable routing architecture for the optical Internet. We focus on a number of key issues that are essential to achieve the desired service scenarios, including the tasks of (a) minimizing the total number of wavelengths used for establishing working and protection paths in WDM networks; (b) minimizing the number of affected working paths in case of a link failure; (c) handling large scale WDM mesh networks; and (d) supporting both Quality of Service (QoS) and best-effort based working lightpaths. To implement the above objectives, a novel path based shared protection framework namely Group Shared protection (GSP) is proposed where the traffic matrix can be divided into multiple protection groups (PGs) based on specific grouping policy, and optimization is performed on these PGs. To the best of our knowledge this is the first work done in the area of group based WDM survivable routing approaches where not only the resource sharing is conducted among the PGs to achieve the best possible capacity efficiency, but also an integrated survivable routing framework is provided by incorporating the above objectives. Simulation results show the effectiveness of the proposed schemes.

En los últimos años la Logística Inversa se ha hecho relevante no solo para el mundo académico sino también para el empresarial. Las empresas dan cada día más importancia a esta área, debido a los factores medioambientales y a los beneficios derivados del mejoramiento de su proceso de devoluciones. Así mismo, para tener unos procesos de Logística Inversa eficientes y exitosos, es necesaria la colaboración entre los miembros de la cadena de suministro. Esta tesis se concentra en ambos aspectos, Colaboración y Logística Inversa.El propósito de esta tesis es doble; primero, analizar los problemas que sufren hoy en día las empresas en esta área, partiendo de una perspectiva general, y posteriormente analizando la industria editorial española. En segundo lugar, nosotros proponemos cuatro modelos matemáticos concernientes a los problemas de planificación que presentan las empresas cuando incorporan las devoluciones, y finalmente proponemos unas metodologías para solucionarlos. / During last years Reverse Logistics has become a relevant topic not only for academics but also for the business world. Companies are giving each day more and more importance to this field, because the environmental issues and the benefits that the company can obtain by the improvement of their return's processes. To obtain a successful and efficient Reverse Logistics processes there exist the need to collaborate along the supply chain. This thesis focuses on both of these two topics, Collaboration and Reverse Logistics. The aim of this thesis is twofold; first, we try to understand the returns processes' problems that companies are facing today from the management point of view, from a general perspective and afterwards on the editorial industry. Secondly, we propose some mathematical models and solution methods related to real planning problems faced by the companies when the returns are incorporated.

Χωροθέτηση μονάδας επεξεργασίας ΑΣΑ σε συνδιασμό με τον απαραίτητο ΧΥΤΥ, με μικτό ακέραιο γραμμικό προγραμματισμό, για τη βελτιστοποίηση των ακολουθούμενων διαδρομών των απορριμματοφόρων προς την μονάδα επεξεργασίας και απο την μονάδα προς τον ΧΥΤΥ.Εγινε με εφαρμογή GIS στη Μεσσηνία. / The current thesis is about optimum siting of a MSW treatment plant combined with a landfill for residues based on mixed integer linear programming (MILP) and GIS methodology.

The current scenario of the Brazilian electricity sector, through the constant and recent regulatory changes imposed by ANEEL in recent years, aims to ensure continuous improvement in quality standards in the provision of electricity, significantly increased surveillance on the power quality delivered to consumers. Following this guideline, ANEEL established X Factor, which set the minimum volume of investments required to electricity distribution companies. In 2010, through the PRORET ANEEL established a new methodology for the calculation of the X Factor, including the Q component, relating to quality of service, setting a milestone in the recent regulatory history of the Brazilian electricity sector, as it allows for the first time gains the annual tariff adjustment or loss according to the performance measured in the year. In this context of regulatory innovations and increasing demands with performance standards and levels of investment made on the electrical system, the correct and efficient use of increasingly scarce resources to improve and expand the electrical system are presented as a vital challenge to financial health of companies. This paper presents a methodology for prioritizing investments in primary networks of electricity distribution, involving two consolidated methodologies aid to decision-making high complexity (AHP and PROMETHEE) and operations research methods to optimize the planning of improvement works to be held in short-term horizon, with direct reflection on regulatory issues, seeking still accommodate regional characteristics of the company and the ability to execute works of each region. / O atual cenário do setor elétrico brasileiro, através das constantes e recentes alterações regulatórias impostas pela ANEEL nos últimos anos, tem como objetivo garantir a melhoria contínua nos padrões de qualidade no fornecimento de energia elétrica, aumentado significativamente a fiscalização sobre a qualidade da energia entregue aos consumidores. Seguindo esta diretriz, a ANEEL instituiu o Fator X, que define o volume de investimentos mínimos exigidos às empresas de distribuição de energia elétrica. Em 2010, através do PRORET a ANEEL estabeleceu uma nova metodologia para o cálculo do Fator X, incluindo o componente Q, referente à qualidade do serviço prestado, configurando como um marco no recente histórico regulatório do setor elétrico brasileiro, pois permite pela primeira vez ganhos no reajuste tarifário anual ou perdas de acordo com o desempenho medido no ano. Neste contexto de inovações regulatórias e exigências cada vez maiores com os padrões de desempenho e níveis de investimentos realizados no sistema elétrico, a aplicação correta e eficiente dos cada vez mais escassos recursos disponíveis para melhoria e ampliação do sistema elétrico se apresentam como um desafio vital à saúde financeira das empresas do setor elétrico. Este trabalho apresenta uma metodologia para priorização de investimentos em redes primárias de distribuição de energia elétrica, associando duas consolidadas metodologias de auxílio à tomada de decisões de elevada complexidade (AHP e PROMETHEE) e métodos de pesquisa operacional para otimização no planejamento de obras de melhoria a serem realizadas no horizonte de curto prazo, com reflexo direto nas questões regulatórias, buscando ainda contemplar características regionais da empresa e a capacidade de execução de obras de cada região.

Le développement de structures de réseau efficaces pour le transport de marchandises est fondamental sur le marché mondial actuel. Les demandes doivent être traitées rapidement, répondre aux besoins des clients dans les meilleurs délais, les congestions et les retards doivent être minimisés, les émissions de CO2 doivent être contrôlés et des coûts de transport moins élevés doivent être proposés aux clients. La structure hub-and-spoke est un modèle de réseau courant utilisé à la fois dans le transport régional comme dans le transport intercontinental, permettant une économie d'échelle grâce aux consolidations opérées au niveau des noeuds hub. Mais, les retards, les congestions et les longs délais de livraison sont des inconvénients de ce type de réseau. Dans cette thèse, un nouveau concept, "sub-hub", est ajouté à la structure du réseau classique hub-and-spoke. Dans les modèles de réseau proposés, une économie d'échelle et des chemins alternatifs plus courts sont mis en oeuvre, en minimisant ainsi le coût de transport et le délai de livraison. Le sub-hub est vu comme un point de connexion entre deux routes distinctes de régions voisines. Des transbordements sans passer par les noeuds hub sont possibles au niveau des sub-hubs. Des congestions peuvent ainsi être évitées et, par conséquent, les retards associés sont ainsi minimisés. Quatre modèles de programmation linéaire en nombres entiers binaires du problème de la localisation de hubs et de routage sont développés dans cette thèse. Des réseaux avec sub-hub et des réseaux sans sub-hub prenant en compte des routes circulaires entre hubs ou des connexions directes entre hubs sont ainsi comparées. Ces modèles sont composés de quatre sous-problèmes (localisation, allocation, conception de service et routage) qui rendent complexe la recherche de solutions. Une approche cutting plane est testée pour résoudre de petites instances de problème tandis qu'une recherche à voisinage variable avec décomposition (VNDS) composée de méthodes exactes (matheuristic) a été développée pour résoudre de grandes instances. Le VNDS mis en oeuvre, explore chaque sous-problème avec différents opérateurs. Des gains importants dans la fonction objective sont observés par les modèles avec sub-hub confirmant ainsi le développement de réseaux plus compétitifs. / The development of efficient network structures for freight transport is a major concern for the current global market. Demands need to be quickly transported and should also meet the customer needs in a short period of time. Traffic congestions and delays must be minimized, since CO2 emissions must be controlled and affordable transport costs have to be offered to customers. Hub-and-spoke structure is a current network model used by both regional and intercontinental transportation, which offers an economy of scale for aggregated demands inside hub nodes. However, delays, traffic congestions and long delivery time are drawbacks from this kind of network. In this thesis, a new concept, which is called "sub-hub", is proposed to the classic hub-and-spoke network structure. In the proposed network models, economy of scale and shorter alternative paths are implemented, thus minimizing the transport cost and delivery time. The sub-hub proposal can be viewed as a connection point between two routes from distinct and close regions. Transshipments without the need to pass through hub nodes are possible inside sub-hubs. This way, congestions can be avoided and, consequently, delays are minimized. Four binary integer linear programming models for hub location and routing problem were developed in this thesis. Networks with sub-hub and networks without sub-hub taking into account circular hub routes or direct connections between hubs are compared. These models are composed of four sub-problems (location, allocation, service design and routing), which hinders the solution. A cutting plane approach was used to solve small instances of problem, while a Variable Neighborhood Decomposition Search (VNDS) composed of exact methods (matheuristic) was developed to solve large instances. The VNDS was used to explore each sub-problem by different operators. Major benefits are provided by models with sub-hub, thus promoting the development of more competitive networks.

Afin d’accélérer les flux de produits, de réduire les niveaux de stocks et de faire des économies de transport, les entreprises de presque toutes les industries ont mis en place des centres de crossdock. Ces centres sont un point intermédiaire de consolidation dans une chaîne logistique. Les constructeurs automobiles Renault et Nissan s’appuient sur un réseau international de plateformes crossdock pour lier des fournisseurs de pièces de première monte avec des usines de production lointaines, généralement en outre-mer. Dans un cadre d’un partenariat académique-industriel entre le laboratoire LIMOS et Renault, cette thèse est focalisée sur la planification et l’ordonnancement des activités dans ces centres de crossdock. Des études de terrain menées chez Renault et Nissan nous ont permis d’identifier les caractéristiques, les contraintes et les inducteurs de coûts des plateformes de crossdock, ainsi que de cibler notre revue de la littérature. Sur ces bases, nous proposons une approche d’optimisation séquentielle, comprenant deux modèles en programmation linéaire en nombres entiers, implémentés dans CPLEX et testés sur des données industrielles de deux plateformes Renault. Les résultats des expérimentations obtenus sur le premier modèle (planification) ont montré une nette amélioration en termes de coûts, par rapport à la méthode Renault. Fort de ce constat, une implémentation industrielle a été faite, avec des résultats aussi probants. Le deuxième modèle (ordonnancement) s’avère pertinent pour des instances de moyenne taille. L’approche proposée permet de répondre à la configuration actuelle des AILN Renault et nous considérons qu’elle est adaptable à d’autres industries. / In order to accelerate product flow, reduce inventory levels and make economies in transportation, companies in almost all industries have set up cross-dock centres. These centres are an intermediate point of consolidation in a supply chain. Car manufacturers Renault and Nissan rely on an international network of crossdock platforms to link suppliers of OEM parts with overseas production plants. In a framework of an academic-industrial partnership between the LIMOS laboratory and Renault, this thesis focuses on the activity planning and scheduling at these crossdock centres.Field studies conducted at Renault and Nissan allowed us to identify the characteristics, constraints and cost drivers of crossdock platforms, as well as to target our review of the literature. Based on this, we propose a sequential optimization approach, comprising two integer linear programming models, implemented in CPLEX and tested on industrial data of two Renault platforms. Numerical experiments’ results obtained on the first model (planning) showed a significant improvement in cost, compared to the Renault method. In light of this results, an industrial implementation was made, with such convincing results. The second model (scheduling) proved to be relevant for medium-sized instances. The proposed approach fits to the current configuration of AILN Renault and we consider that it is adaptable to other industries.

Les Réseaux de Chaleur (RdC) connaissent un nouvel essor en France qui s’explique par leur capacité à valoriser, à un prix raisonnable, des énergies bas carbone dans les domaines du chauffage et de l’eau chaude sanitaire aujourd’hui fortement émetteurs de CO2. L’amélioration du contrôle de ces systèmes complexes est un enjeu clé pour accroître leur compétitivité et favoriser leur développement. Cette thèse s’intéresse à la gestion par commande optimale des RdC. Pour cette application, nous avons développé et évalué un algorithme qui, à partir d’une prévision de la demande, optimise l’utilisation des différents moyens de production ainsi que la température de départ et la pression différentielle. Par rapport aux systèmes existants, les originalités de notre solution sont de tirer pleinement partie des capacités de stockage thermique dans le réseau et de déterminer le meilleur compromis entre coûts liés au pompage et pertes thermiques. Cette thèse débute par un travail de modélisation dynamique réalisé à l’échelle composant. En nous appuyant sur une démarche de validation expérimentale, nous avons systématiquement recherché le meilleur compromis entre précision et efficacité numérique (Chapitre 1). Le cas d’étude, décrit dans le Chapitre 2, est un RdC virtuel à l’échelle d’un quartier, représentatif du cas Grenoble. Pour le développement du système de gestion avancée, nous présentons ensuite une version linéarisée du modèle de réseau de distribution que nous intégrons à un optimiseur en suivant le formalisme de la programmation linéaire mixte. L’algorithme de gestion proposé est ensuite décrit (Chapitre 3). Il associe un modèle dynamique non-linéaire et l’optimiseur précité. L’objet du quatrième chapitre est l’évaluation des performances de notre algorithme par la simulation et la comparaison à des méthodes de contrôle existantes. Enfin, un dernier chapitre étudie la robustesse de l’algorithme en condition de commande réelle, c’est-à-dire en tenant compte de différentes sources d’incertitude. / District Heating (DH) are currently fast-growing in France. This situation is explained by their ability to exploit and disseminate massively, at a reasonable price, energy sources with low CO2 contents in the sectors of space heating and domestic hot water production, nowadays strongly emitters of greenhouse gases. Improving the control of these complex energy systems is a key issue for increasing their competitiveness and promote their development.This thesis focuses on the optimal control of DH systems. For this application, we have developed and tested an algorithm that optimizes, given a load prediction, the use of the production means, the supply temperature and the differential pressure. Compared to existing methods, the original features of the developed solution are to fully exploit the thermal storage capacity of the network and to determine the best compromise between costs for pumping and heat losses.This thesis begins with a work on dynamic modeling carried out at the component scale. Based on an experimental validation approach, we systematically sought the best compromise between accuracy and computational efficiency (Chapter 1). The case study, described in Chapter 2, is a virtual DH at the district scale, representing the Grenoble case. For the development of the advanced control system, we then present a linearized version of the distribution network model that we integrate into an optimizer relying on Mixed Linear Programming. The proposed control algorithm is described in Chapter 3. It combines a nonlinear dynamic model and the aforementioned optimizer. The topic of the fourth chapter is the evaluation of the performance of our algorithm by simulation and comparison with existing methods of control. A final chapter examines the robustness of the algorithm in real control conditions considering various sources of uncertainty.