This study considers a vehicle routing problem with time windows, accessibility restrictions on customers and a fleet that is heterogeneous with regard to capacity, average speed and cost. A vehicle can perform multiple routes per day, all starting and ending at a single depot, and it is assigned to a single driver, whose total work hours are limited. The available fleet is divided into an owned fleet, for which a variable cost is incurred, and a chartered fleet, for which only a fixed cost is incurred for each vehicle used. A column generation algorithm embedded in a branch-and-bound framework is proposed. The column generation pricing subproblem required a specific elementary shortest path problem with resource constraints algorithm to address the possibility for each vehicle performing multiple routes per day and to address the need to determine the workdays start time within the planning horizon. To make the algorithm efficient, a constructive heuristic and a learning metaheuristic algorithm based on tabu search were also developed. Both were used on branch-and-bound tree nodes to generate a good initial solution to the linear restricted master problem; particularly, to find a good initial primal bound to the branch-and-bound tree. / Este estudo aborda um problema de roteirização de veículos com janelas de tempo, restrições de acessibilidade nos clientes e uma frota que é heterogênea em relação à capacidade de carga, velocidade média de deslocamento e custo. Um veículo pode percorrer múltiplas rotas por dia, todas começando e terminando em um mesmo depósito, e está designado a um único motorista, cujo total de horas trabalhadas no dia está limitado a um valor máximo. A frota disponível é dividida em uma frota própria, para a qual um custo variável é incorrido, e uma frota de freteiros, para a qual apenas um custo fixo é incorrido para cada veículo utilizado. Um algoritmo baseado em geração de colunas, integrado a um procedimento de branch-and-bound, é proposto neste estudo. O subproblema de precificação da geração de colunas requereu um algoritmo específico para o problema do caminho mínimo elementar com restrições sobre recursos capaz de lidar com a possibilidade de cada veículo percorrer múltiplas rotas por dia e capaz de lidar com a necessidade de determinar o instante de início do dia de trabalho do motorista dentro do horizonte de planejamento. Para tornar o algoritmo eficiente, uma heurística construtiva e uma heurística de melhoria baseada em busca tabu também foram desenvolvidos. Ambos são utilizados nos nós da árvore de branch-and-bound para gerar boas soluções iniciais para o problema mestre restrito da geração de colunas; particularmente, para encontrar um bom limitante primal inicial para a árvore de branch-and-bound.

Made available in DSpace on 2015-03-05T13:57:00Z (GMT). No. of bitstreams: 0 Previous issue date: 27 / Nenhuma / Problemas de pessoal, produtividade e contenção de custos afetam todas as áreas de negócio, inclusive os provedores de cuidados de saúde. Porém, nesta área o controle dos custos não pode comprometer a qualidade do atendimento. É neste contexto que uma ferramenta computacional para a elaboração das escalas de trabalho de pessoal de enfermagem torna-se importante. Esta é uma tarefa realizada manualmente na maioria dos hospitais e clínicas, consumindo muito tempo e nem sempre atendendo completamente a legislação e normas vigentes. No Brasil há falta de ferramentas computacionais para a elaboração destas escalas, ou mesmo para a avaliação das escalas desenvolvidas. O objetivo desta pesquisa é encontrar uma solução, computacionalmente viável, para a geração de escalas de trabalho mensais para os técnicos de enfermagem, de acordo com as regras operacionais dos hospitais e as restrições da legislação. Deseja-se ainda obter maior nível de satisfação dos funcionários atendendo preferências de dias de folga e distribui / Problems of personnel, productivity and cost restriction affect all areas of a business, including the health care providers. However, in this area, cost control cannot endanger the quality of service. In this context, a software for creating the schedule of nursing personnel becomes important. This is a hand-made task in the majority of hospitals and clinics. It is time consuming and does not always comply to the legislation and the valid rules. In Brazil, there is a lack of computer tools for the creation of these schedules or even for the evaluation of the ones already developed. This research aims at finding a technologically feasible solution for the generation of monthly schedules for the nursing technicians, according to the operational rules of hospitals and legislation restrictions. It also aims at giving the employees a higher level of satisfaction, concerning their day off preferences and equitable distribution of duties on Saturdays, Sundays and holidays. The proposal is to apply a Tabu Search me

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2015-07-03T17:52:39Z No. of bitstreams: 1 Iris Corrêa das Chagas Linck.pdf: 1456080 bytes, checksum: ea4a6f659a229e845649c58baaf8cb23 (MD5) / Made available in DSpace on 2015-07-03T17:52:39Z (GMT). No. of bitstreams: 1 Iris Corrêa das Chagas Linck.pdf: 1456080 bytes, checksum: ea4a6f659a229e845649c58baaf8cb23 (MD5) Previous issue date: 2012 / FINEP - Financiadora de Estudos e Projetos / Neste trabalho é desenvolvido um algoritmo híbrido que simula o comportamento do Codificador/Decodificador de vídeo H.264/AVC, ou simplesmente CODEC H.264, utilizado no Sistema Brasileiro de Televisão Digital. O algoritmo proposto tem a finalidade de buscar a melhor configuração possível de seis dos principais parâmetros utilizados para a configuração do CODEC H.264. Este problema é abordado como um problema de otimização combinatória conhecido como Problema de Seleção de Partes e que é classificado como NP-Difícil. O algoritmo híbrido proposto, denominado Simulador de Metaheurísticas aplicado a um CODEC (SMC), foi desenvolvido com base em duas metaheurísticas: Busca Tabu e Algoritmo Genético. Os seis parâmetros de configuração a serem otimizados pelo SMC são: o bit rate; o frame rate; os parâmetros de quantização de quadros tipo B, tipo P e tipo I e a quantidade de quadros tipo B em um grupo de imagens (GOP – Group of Pictures). Os dois primeiros parâmetros mencionados atuam basicamente sobre a qualidade da imagem do vídeo enquanto que os demais parâmetros atuam diretamente na compressão do vídeo. Experimentos e testes foram feitos utilizandose o CODEC H.264 desenvolvido no Projeto Plataforma de Convergência Digital IPTV/TV Digital (DigConv). Nos experimentos o CODEC tem seus parâmetros configurados de acordo com os resultados obtidos pelo SMC. Um vídeo é codificado no CODEC H.264 para que se possa analisar a sua qualidade de imagem e o seu grau de compressão após o processo de codificação. É feita uma correlação entre esses resultados e a Função Objetivo do SMC. A qualidade da imagem é medida através da métrica mais utilizada na literatura, o PSNR (Peak Signal to Noise Ratio), que é calculada pelo próprio CODEC ao final da codificação de um vídeo. Verificouse que à medida que a Função Objetivo aumenta, o CODEC H.264 consegue obter uma melhor qualidade de imagem e um maior grau de compressão de vídeo. / In this work is developed a hybrid algorithm that simulates the behavior of the H.264/AVC video encoder/decoder, or simply H.264 video CODEC, used in the Brazilian System of Digital Television. The proposed algorithm intends to seek the best possible configuration of the six main parameters used for configuring the H.264 video CODEC. This problem is treated as a combinatorial optimization problem known as the Parties Selection Problem, which is classified as NP-Hard. The proposed hybrid algorithm, called Simulator Metaheuristcs applied to a CODEC (SMC), was developed based on two metaheuristics: Tabu Search and Genetic Algorithm. The six configuration parameters to be optimized by the SMC are the bit rate, frame rate, the parameters of quantization tables of type B, type I and type P and the amount of frames type B in a group of pictures (GOP - Group of Pictures).The first two parameters mentioned, work primarily on the quality of the video image while the other parameters act directly on the video compression. Experiments and tests were done using the video CODEC H.264 developed in Digital Convergence Platform IPTV/Digital TV Project (DigConv). DigConv Project. In the experiments the CODEC has its parameters set according to the results obtained by the SMC. Then, a video is encoded by the CODEC in order to analyze the video image quality and the video compression degree reached after the encoding process. It is made a correlation between these results and the objective function of the SMC. The picture quality is measured by the metric most often used in literature, the PSNR (Peak Signal to Noise Ratio), which is calculated by the CODEC at the end of a video encoding process. It was found that as the objective function has increased, the CODEC reached a better image quality and a higher video compression.

Submitted by Silvana Teresinha Dornelles Studzinski (sstudzinski) on 2016-11-18T11:12:32Z No. of bitstreams: 1 Robermilton Sant´Anna de Oliveira Rodrigues_.pdf: 3942890 bytes, checksum: cd68235e6f58b7b97f966958f932b60d (MD5) / Made available in DSpace on 2016-11-18T11:12:32Z (GMT). No. of bitstreams: 1 Robermilton Sant´Anna de Oliveira Rodrigues_.pdf: 3942890 bytes, checksum: cd68235e6f58b7b97f966958f932b60d (MD5) Previous issue date: 2016-06-10 / IFRR - Instituto Federal de Educação Ciência e Tecnologia de Roraima / Com o advento da Internet, aliado à constante evolução das tecnologias de distribuição de Banda Larga, juntamente com um público cada vez mais exigente, surge o IPTV (Internet Protocol Television). Atualmente, existem várias pesquisas sobre como melhorar sua distribuição de conteúdo, através dos mais diversos dispositivos disponíveis no mercado, tais como: TV Digital, Tablets e Smartphones. Este trabalho apresenta uma ferramenta computacional, baseada em um modelo matemático, para otimização dos parâmetros do módulo IPTV de uma Plataforma de Convergência Digital (DIGICONV). Essa ferramenta computacional é baseada em aplicações das metaheurísticas Busca Tabu e Algoritmo Genético, a fim de obter melhorias em todos os segmentos da transmissão, além de identificar os motivos de uma possível sobrecarga do sistema, quando não há banda disponível suficiente para atender a todos os clientes, através de configurações específicas nos parâmetros de entrada que são: a taxa de transmissão (Tt), a qualidade de vídeo (Qv), a qualidade de áudio (Qa), os tipos de clientes (Tc), a largura de banda do cliente (Lb) e a quantidade de banda disponível (Bd). Os resultados obtidos neste trabalho comprovaram que tanto a Busca Tabu quanto o Algoritmo Genético obtiveram resultados satisfatórios e otimizados, conforme o aumento da Função Objetivo, atestando sua eficiência. / With the advent of the Internet, combined with the constant evolution of the broadband distribution technologies, along with the public increasingly demanding, IPTV (Internet Protocol Television) arises. Currently, there are several studies on how to improve the distribution of content through a variety of devices available in the market, such as Digital TV, Tablets and Smartphones. This paper presents a computational tool based on a mathematical model to optimize IPTV module parameters of a Digital Convergence Platform (DIGICONV). This software tool is based on applications of metaheuristics Tabu Search and Genetic Algorithm in order to achieve improvements in all segments of the transmission, and to identify the reasons for a possible system overload, when there is not enough available bandwidth to meet all customers through specific settings in the input parameters are: the transmission rate (Tt), the video quality (Qv), audio quality (Qa), the types of customers (Tc), the bandwidth of client (Lb) and the amount of available bandwidth (BD). The results of this study showed that both the tabu search and the genetic algorithm achieved satisfactory results and optimized, with increasing Objective Function, attesting to its effectiveness.

As technology scales down and CMOS circuits are powered by lower supply voltages, standby leakage current becomes significant. A behavioral level framework for the synthesis of data-paths with low leakage power is presented. There has been minimal work done on the behavioral synthesis of low leakage datapaths. We present a fast architectural simulator for leakage (FASL) to estimate the leakage power dissipated by a system described hierarchically in VHDL. FASL uses a leakage power model embedded into VHDL leafcells. These leafcells are characterized for leakage accurately using HSPICE. We present results which show that FASL measures leakage power significantly faster than HSPICE, with less than a 5% loss in accuracy, compared to HSPICE. We present a comprehensive framework for synthesizing low leakage power data-paths using a parameterized Multi-threshold CMOS (MTCMOS) component library. The component library has been characterized for leakage power and delay as a function of sleep transistor width. We propose four techniques for minimization of leakage power during behavioral synthesis: (1) leakage power management using MTCMOS modules; (2) an allocation and binding algorithm for low leakage based on clique partitioning; (3) selective binding to MTCMOS technology, allowing the designer to have control over the area overhead; and (4) a performance recovery technique based on multi-cycling and introduction of slack, to alleviate the loss in performance attributed to the introduction of MTCMOS modules in the data-path. Finally, we propose two iterative search based techniques, based on Tabu search, to synthesize low leakage data-paths. The first technique searches for low leakage scheduling options. The second technique simultaneously searches for a low leakage schedule and binding. It is shown that the latter technique of unified search is more robust. The quality of results generated bytabu-based technique are superior to those generated by simulated annealing (SA) search technique.

In this thesis, a new tool, named CHESS, is designed and developed for control and data-flow graph (CDFG) extraction and the high-level synthesis of VLSI systems. The tool consists of three individual modules for:(i) CDFG extraction, (ii) scheduling and allocation of the CDFG, and (iii) binding, which are integrated to form a comprehensive high-level synthesis system. The first module for CDFG extraction includes a new algorithm in which certain compiler-level transformations are applied first, followed by a series of behavioral-preserving transformations on the given VHDL description. Experimental results indicate that the proposed conversion tool is quite accurate and fast. The CDFG is fed to the second module which schedules it for resource optimization under a given set of time constraints. The scheduling algorithm is an improvement over the Tabu Search based algorithm described in [6] in terms of execution time. The improvement is achieved by moving the step of identifying mutually exclusive operations to the CDFG extraction phase, which, otherwise, is normally done during scheduling. The last module of the proposed tool implements a new binding algorithm based on a game-theoretic approach. The problem of binding is formulated as a non-cooperative finite game, for which a Nash-Equilibrium function is applied to achieve a power-optimized binding solution. Experimental results for several high-level synthesis benchmarks are presented which establish the efficacy of the proposed synthesis tool.

La superposition de topologies virtuelles à la topologie physique d'un réseau est un des principaux mécanismes de l'ingénierie de trafic. Soit un réseau physique d'une certaine topologie et capacité fixées et une matrice de trafic à véhiculer, il s'agit trouver une topologie logique permettant de mapper de manière optimale la matrice de trafic sur le réseau physique. Lors de l'évolution de la matrice de trafic sur des échelles de temps longues, il faudra agir sur le layout. La première contribution concerne la définition de fonctions de coût mieux adaptées à la réalité d'un opérateur, la deuxième contribution concerne la prise en compte du coût de changement du layout. Il s'avère intéressant d'un point de vue opérateur de réduire la complexité du layout, mesurée comme une fonction du nombre de chemins virtuels. Nous avons donc formulé divers problèmes de minimisation de la complexité du layout sous des contraintes de QoS. Il s'agit d'une modélisation réaliste mais qui engendre des modèles difficiles à résoudre. Nous avons développés des heuristiques qui permet de trouver des solutions approchées pour des réseaux de grande taille. Nous avons montré que la complexité des layouts peut être significativement réduite en comparaison avec celle obtenue suite à l'optimisation des fonctions de coût classiques. Le changement du layout implique d'une part un coût d'opération et d'autre part peut engendrer des coupures de service qui affecteront directement le coût d'opération. Nous avons formulé une famille de problèmes prenant en compte le coût de reconfiguration du layout. L'une des heuristiques citées a été adaptée pour analyser ces nouveaux problèmes.

A spacecraft tour trajectory is a trajectory in which a spacecraft visits a number of objects in sequence. The target objects may consist of satellites, moons, planets or any other body in orbit, and the spacecraft may visit these in a variety of ways, for example flying by or rendezvousing with them. The key characteristic is the target object sequence which can be represented as a discrete set of decisions that must be made along the trajectory. When this sequence is free to be chosen, the result is a hybrid discrete-continuous optimization problem that combines the challenges of discrete and combinatorial optimization with continuous optimization. The problem can be viewed as a generalization of the traveling salesman problem; such problems are NP-hard and their computational complexity grows exponentially with the problem size. The focus of this dissertation is the development of a novel methodology for the solution of spacecraft tour trajectory optimization problems. A general model for spacecraft tour trajectories is first developed which defines the parameterization and decision variables for use in the rest of the work. A global search methodology based on the tabu search metaheuristic is then developed. The tabu search approach is extended to operate on a tree-based solution representation and neighborhood structure, which is shown to be especially efficient for problems with expensive solution evaluations. Concepts of tabu search including recency-based tabu memory and strategic intensification and diversification are then applied to ensure a diverse exploration of the search space. The result is an automated, adaptive and efficient search algorithm for spacecraft tour trajectory optimization problems. The algorithm is deterministic, and results in a diverse population of feasible solutions upon termination. A novel numerical search space pruning approach is then developed, based on computing upper bounds to the reachable domain of the spacecraft, to accelerate the search. Finally, the overall methodology is applied to the fourth annual Global Trajectory Optimization Competition (GTOC4), resulting in previously unknown solutions to the problem, including one exceeding the best known in the literature. / text

Increasing debates over a gasoline independent future and the reduction of greenhouse gas (GHG) emissions has led to a surge in plug-in hybrid electric vehicles (PHEVs) being developed around the world. Due to the limited all-electric range of PHEVs, a daytime PHEV charging infrastructure will be required for most PHEVs’ daily usage. This dissertation, for the first time, presents a mixed integer mathematical programming model to solve the PHEV charging infrastructure planning (PCIP) problem. Our case study, based on the Oak Ridge National Laboratory (ORNL) campus, produced encouraging results, indicates the viability of the modeling approach and substantiates the importance of considering both employee convenience and appropriate grid connections in the PCIP problem. Unfortunately, the classical optimization methods do not scale up well to larger practical problems. In order to effectively and efficiently attack larger PCIP problems, we develop a new MASTS based TS algorithm, PCIP-TS to solve the PCIP. The results from computational experiments for the ORNL campus problem establish the dominant supremacy of the PCIP-TS method both in terms of solution quality and computational time. Additional experiments with simulated data representative of a problem that might be faced by a small city show that PCIP-TS outperforms CPLEX based optimization. Once the charging infrastructure is in place, the immediate problem is to judiciously manage this system on a daily basis. This thesis formally develops a mixed integer linear program to solve the daily the energy management problem (DEM) faced by an organization and presented results of a case study performed for ORNL campus. The results from our case study, based on the Oak Ridge National Laboratory (ORNL) campus, are encouraging and substantiate the importance of controlled PHEV fleet charging and realizing V2G capabilities as opposed to uncontrolled charging methods. Although optimal solutions are obtained, the solver requires practically unacceptable computational times for larger problems. Hence, we develop a new MASTS based TS algorithm, DEM-TS, for the DEM models. Results for ORNL campus data set prove the dominant computational efficiency of the DEM-TS. For the simulated extended sized problems that resemble the complexity of a problem faced by a small city, the results prove that DEM-T not only achieves optimality, but also produces sets of multiple alternate optimal solutions. These could be very helpful in practical settings when alternate solutions are necessary because some solutions may not be deployable due to unforeseen circumstances. / text

Šiame darbe nagrinėjamas patobulintas tabu paieškos metodas, žinomas kaip iteratyvioji tabu paieška (ITP). Pasiūlytos kai kurios ITP metodo modifikacijos, besiremiančios tam tikromis sprendinių mutavimo (pertvarkymo) procedūromis (inversijos, įterpimai ir kt.), kurios įgalina pagerinti gaunamų sprendinių kokybę. Atlikti išsamūs sudaryto ITP algoritmo ir kitų pasiūlytų modifikacijų eksperimentiniai tyrimai, panaudojant testinius KU pavyzdžius iš KU testinių pavyzdžių bibliotekos TSPLIB. Gauti rezultatai patvirtina pasiūlytų modifikacijų pranašumą kitų ITP variantų atžvilgiu. / In this work, one of the heuristic algorithm – the iterated tabu search and its modifications are discussed. The work is organized as follows. Firstly, some basic definitions and preliminaries are given. Then, the iterated tabu search algoritm and its variants based on special type mutations are considered in more details. The ITS algorithms modifications were tested on the TSP instances from the TSP library TSPLIB. The results of this tests (experiments) are presented as well. The work is completed with the conclusions.