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Aplicação de metaheurísticas na resolução do problema de balanceamento e designação de trabalhadores com deficiência em linha de produção /Silva, Renato Teixeira da. January 2012 (has links)
Orientador: Galeno José de Sena / Banca: Marcos Antonio Pereira / Banca: Anibal Tavares de Azevedo / Resumo: A Organização Internacional do Trabalho estima que existem cerca de 650 milhões de pessoas com deficiência em idade produtiva. No entanto, esta parcela da população possui altos índices de desemprego devido a várias barreiras. Uma alternativa para facilitar a inclusão dessas pessoas é a criação de Centros de Trabalho para pessoas com Deficiência (CTD's) onde as pessoas com deficiência tenham a oportunidade de experimentar um ambiente de trabalho real antes de irem para um emprego "normal". Neste tipo de ambiente, onde é impossível ao gestor prever quais trabalhadores estarão disponíveis a cada dia devido às altas taxas de absenteísmo, há a necessidade de se definir uma organização mais produtiva diariamente. Neste contexto se torna oportuna a utilização do Problema de Balanceamento de Linha e Designação de Trabalhadores (em inglês ALWABP), onde se busca minimizar o tempo de ciclo a partir de um dado número de trabalhadores, alocando tarefas às estações de trabalho e trabalhadores às estações, tendo em vista que alguns trabalhadores podem ser muito lentos para executar certas tarefas ou até incapazes, devido a alguma deficiência que eles apresentam, e muito eficientes na execução de outras. O objetivo geral desta dissertação consiste em empregar diferentes metaheurísticas para resolver o ALWABP, comparando com os melhores resultados das instâncias encontradas na literatura. Dentre várias metaheurísticas disponíveis na literatura foram utilizados o Harmony Search (HS), o Adaptive Large Neighborhood Search (ALNS) e o Clustering Search (CS) utilizando o HS e o ALNS como heurísticas geradoras de soluções. Cada uma das quatro implementações foram testadas em 320 instâncias propostas na literatura divididas em quatro famílias. Os experimentos computacionais mostraram bons resultados... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The International Labour Organization estimates that there are approximately 650 million disabled people in working age. However, this population presents high rates of unemployment due to numerous barriers. An alternative to facilitate the inclusion of these people is the establishment of Centers for Working People with Disabilities where people with disabilities have the opportunity to experience a real work environment before going to a "normal" job. In this type of environment, where it is impossible to predict which workers will be available each day due to high rates of absence in this population, there is a need to define a more productive organization on a daily basis. In this context it becomes appropriate to use the Assembly Line Worker Assignment and Balancing Problem (ALWABP), which seeks to minimize the cycle time for a given number of workers, assigning tasks to workstations and workers to stations, considering that some workers may be too slow to perform certain tasks, or even unable due to some deficiency they present, and very efficient in performing others. The aim of this dissertation is to employ different metaheuristics to solve the ALWABP, comparing with the best results of instances found in the literature. Among several metaheuristics available in the literature were used Harmony Search (HS), Adaptive Large Neighborhood Search (ALNS) and Clustering Search (CS) using the HS and ALNS as heuristics for the generation of solutions. Each of the four implementations has been tested in 320 instances proposed in the literature, classified into four families. The computational experiments showed good results, and in some instances obtaining better solution values best known. Conclusions regarding... (Complete abstract click electronic access below) / Mestre

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Aplicação de metaheurísticas na resolução do problema de balanceamento e designação de trabalhadores com deficiência em linha de produçãoSilva, Renato Teixeira da [UNESP] 26 October 2012 (has links) (PDF)
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silva_rt_me_guara.pdf: 445223 bytes, checksum: f6563e16194940a8f4f8abc7c03ac033 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A Organização Internacional do Trabalho estima que existem cerca de 650 milhões de pessoas com deficiência em idade produtiva. No entanto, esta parcela da população possui altos índices de desemprego devido a várias barreiras. Uma alternativa para facilitar a inclusão dessas pessoas é a criação de Centros de Trabalho para pessoas com Deficiência (CTD`s) onde as pessoas com deficiência tenham a oportunidade de experimentar um ambiente de trabalho real antes de irem para um emprego “normal”. Neste tipo de ambiente, onde é impossível ao gestor prever quais trabalhadores estarão disponíveis a cada dia devido às altas taxas de absenteísmo, há a necessidade de se definir uma organização mais produtiva diariamente. Neste contexto se torna oportuna a utilização do Problema de Balanceamento de Linha e Designação de Trabalhadores (em inglês ALWABP), onde se busca minimizar o tempo de ciclo a partir de um dado número de trabalhadores, alocando tarefas às estações de trabalho e trabalhadores às estações, tendo em vista que alguns trabalhadores podem ser muito lentos para executar certas tarefas ou até incapazes, devido a alguma deficiência que eles apresentam, e muito eficientes na execução de outras. O objetivo geral desta dissertação consiste em empregar diferentes metaheurísticas para resolver o ALWABP, comparando com os melhores resultados das instâncias encontradas na literatura. Dentre várias metaheurísticas disponíveis na literatura foram utilizados o Harmony Search (HS), o Adaptive Large Neighborhood Search (ALNS) e o Clustering Search (CS) utilizando o HS e o ALNS como heurísticas geradoras de soluções. Cada uma das quatro implementações foram testadas em 320 instâncias propostas na literatura divididas em quatro famílias. Os experimentos computacionais mostraram bons resultados... / The International Labour Organization estimates that there are approximately 650 million disabled people in working age. However, this population presents high rates of unemployment due to numerous barriers. An alternative to facilitate the inclusion of these people is the establishment of Centers for Working People with Disabilities where people with disabilities have the opportunity to experience a real work environment before going to a “normal” job. In this type of environment, where it is impossible to predict which workers will be available each day due to high rates of absence in this population, there is a need to define a more productive organization on a daily basis. In this context it becomes appropriate to use the Assembly Line Worker Assignment and Balancing Problem (ALWABP), which seeks to minimize the cycle time for a given number of workers, assigning tasks to workstations and workers to stations, considering that some workers may be too slow to perform certain tasks, or even unable due to some deficiency they present, and very efficient in performing others. The aim of this dissertation is to employ different metaheuristics to solve the ALWABP, comparing with the best results of instances found in the literature. Among several metaheuristics available in the literature were used Harmony Search (HS), Adaptive Large Neighborhood Search (ALNS) and Clustering Search (CS) using the HS and ALNS as heuristics for the generation of solutions. Each of the four implementations has been tested in 320 instances proposed in the literature, classified into four families. The computational experiments showed good results, and in some instances obtaining better solution values best known. Conclusions regarding... (Complete abstract click electronic access below)

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Vertex Ordering for a Partitioningbased Fitting Algorithm for an EPLD DeviceGao, Tongjun 05 November 1993 (has links)
As the ApplicationSpecific Integrated Circuit(ASIC) technology develops to the trend of high density and modulization, the ASIC device market has been dominated gradually by the more complex Erasable Programmable Logic Devices (EPLDs) and the Field Programmable Gate Array(FPGAs) instead of the ordinally Programmable Logic Devices(PLDs). Meanwhile, the design automation system for such programmable devices has also moved from schematic entry design to high level hardware description language entry design. Usually, the whole design automation process consists of three phrases, the high level hardware description language compiler, the logic synthesis stage and the layout synthesis stage. Though the layout synthesis stage contains placement and routing, for some highly restricted connection architecture devices, placement and routing have to be considered together as a fitting problem. This thesis concentrated on the utilization of the Heuristic methods, which can be described as vertex ordering and global vertices number estimation, on an ArchitectureDriven Partitioning fitting algorithm. The test results showed that the heuristic algorithm can beat the comparable algorithm in several fields. These prove the correctness of our heuristic methods and they can be used to guide the future work on the fitting problem of other similar programmable devices.

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Learning To GraspVarley, Jacob Joseph January 2018 (has links)
Providing robots with the ability to grasp objects has, despite decades of research, remained a challenging problem. The problem is approachable in constrained environments where there is ample prior knowledge of the scene and objects that will be manipulated. The challenge is in building systems that scale beyond specific situational instances and gracefully operate in novel conditions. In the past, heuristic and simple rule based strategies were used to accomplish tasks such as scene segmentation or reasoning about occlusion. These heuristic strategies work in constrained environments where a roboticist can make simplifying assumptions about everything from the geometries of the objects to be interacted with, level of clutter, camera position, lighting, and a myriad of other relevant variables. With these assumptions in place, it becomes tractable for a roboticist to hardcode desired behaviour and build a robotic system capable of completing repetitive tasks. These hardcoded behaviours will quickly fail if the assumptions about the environment are invalidated. In this thesis we will demonstrate how a robust grasping system can be built that is capable of operating under a more variable set of conditions without requiring significant engineering of behavior by a roboticist.
This robustness is enabled by a new found ability to empower novel machine learning techniques with massive amounts of synthetic training data. The ability of simulators to create realistic sensory data enables the generation of massive corpora of labeled training data for various grasping related tasks. The use of simulation allows for the creation of a wide variety of environments and experiences exposing the robotic system to a large number of scenarios before ever operating in the real world. This thesis demonstrates that it is now possible to build systems that work in the real world trained using deep learning on synthetic data. The sheer volume of data that can be produced via simulation enables the use of powerful deep learning techniques whose performance scales with the amount of data available. This thesis will explore how deep learning and other techniques can be used to encode these massive datasets for efficient runtime use. The ability to train and test on synthetic data allows for quick iterative development of new perception, planning and grasp execution algorithms that work in a large number of environments. Creative applications of machine learning and massive synthetic datasets are allowing robotic systems to learn skills, and move beyond repetitive hardcoded tasks.

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Project Scheduling Under Constrained ResourcesBenameur, Mohammed 01 October 1980 (has links)
This report examines the widely acceptable Heuristic and Exact procedures for solving the problem of project scheduling and control under constrained resources. Heuristic approaches are more practical, however they depend on the type of the project as well as the resources involved. Exact procedures are illustrated using an Integer Linear Programming formulation of the problem, and also solving it using the Branch and Bound Technique. Impracticality of the exact methods stews from the fact that the computations expand to an unmanageable amount.

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Project Network Scheduling with Limited Resources Using Heuristic Solution TechniquesRojas, Enrique J. Daboin 01 April 1981 (has links)
Traditional critical path methods imply the assumption of unlimited availability of resources. Mathematical models and heuristic techniques are two alternatives that consider resource limitation to sequence the activities of a project. This research explores the consideration of project scheduling under resource constraints for the specific case of single resource, single project scheduling. A computer model called GENRESII search model is developed using a modification of Brooks' algorithm to develop project schedules. The criteria used are various weighted combinations of ACTIM, ACTRES and ACTFOL. An improvement of GENRESII solutions is obtained when the best set of GENII values is input to a computer model called COMSOAL simulation model. The criteria developed generates a large number of feasible solutions rapidly. The probability of generating optimal solutions is related to the size of the generated sample. Eight network cases were considered to validate both computer models. Special attention was given to those activities that were considered critical at a specific time. The number of resources available was increased to a new higher limit in order to schedule activities that became critical. The GENRESII model was effective in finding project durations equal to or less than ACTIM, ACTRES, GENRES or ACTFOL. The COMSOAL model was found very effective in most of the cases in improving the GENII solutions.

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A heuristic for the assignment problem and related bounds /Lai, Cheong Wai. January 1981 (has links)
No description available.

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A new twophase heuristic for twodimensional rectangular binpacking and strippacking /Sadones, Sylvie. January 1985 (has links)
No description available.

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Formal symbolic verification using heuristic search and abstraction techniquesQian, Kairong, Computer Science & Engineering, Faculty of Engineering, UNSW January 2006 (has links)
Computing devices are pervading our everyday life and imposing challenges for designers that have the responsibility of producing reliable hardware and software systems. As systems grow in size and complexity, it becomes increasingly difficult to verify whether a design works as intended. Conventional verification methods, such as simulation and testing, exercise only parts of the system and from these parts, draw conclusions about the correctness of the total design. For complex designs, the parts of the system that can be verified are relatively small. Formal verification aims to overcome this problem. Instead of exercising the system, formal verification builds mathematical models of designs and proves whether properties hold in these models. In doing so, it at least aims to cover the complete design. Model checking is a formal verification method that automatically verifies a model of a design, or generates diagnostic information if the model cannot be verified. It is because of this usability and level of automation that model checking has gained a high degree of success in verifying circuit designs. The major disadvantage of model checking is its poor scalability. This is due to its algorithmic nature: namely, every state of the model needs to be enumerated. In practice, properties of interest may not need the exhaustive enumeration of the model state space. Many properties can be verified (or falsified) by examining a small number of states. In such cases, exhaustive algorithms can be replaced with search algorithms that are directed by heuristics. Methods based on heuristics generally scale well. This thesis investigates nonexhaustive model checking algorithms and focuses on error detection in system verification. The approach is based on a novel integration of symbolic model checking, heuristic search and abstraction techniques to produce a framework that we call abstractiondirected model checking. There are 3 main components in this framework. First, binary decision diagrams (BDDs) and heuristic search are combined to develop a symbolic heuristic search algorithm. This algorithm is used to detect errors. Second, abstraction techniques are applied in an iterative way. In the initial phase, the model is abstracted, and this model is verified using exhaustive algorithms. If a definitive verification result cannot be obtained, the same abstraction is reused to generate a search heuristic. The heuristic in turn is used to direct a search algorithm that searches for error states in the concrete model. Third, a model transformation mechanism converts an arbitrary branchingtime property to a reachability property. Essentially, this component allows this framework to be applied to a more general class of temporal property. By amalgamating these three components, the framework offers a new verification methodology that speeds up error detection in formal verification. The current implementation of this framework indicates that it can outperform existing standard techniques both in runtime and memory consumption, and scales much better than conventional model checking.

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Heuristics for laying out information graphs /Lavinus, Joseph W., January 1992 (has links)
Thesis (M.S.)Virginia Polytechnic Institute and State University, 1992. / Vita. Abstract. Includes bibliographical references (leaves 7376). Also available via the Internet.

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