Este trabalho lida com o problema de balanceamento e sequenciamento de linhas de produção multi-modelo com trabalhadores deficientes, uma generalização de dois importantes problemas da literatura de linhas de produção: o Problema de Balanceamento de Linhas de Produção Multi-Modelo (MALBP) e o Problema de Balanceamento e Designação de Trabalhadores em Linhas de Produção (ALWABP). O MALBP tem sido particularmente importante nas últimas décadas, onde, em um cenário de maior competividade, cresce a necessidade de produção em larga escala de produtos customizados. O ALWABP, por sua vez, é de grande importância em Centros de Trabalhadores com Deficiências (CTDs), onde é necessário considerar as competências individuais de cada trabalhador, que se revelam nos diferentes tempos de execução de uma tarefa, segundo o trabalhador escolhido. Ao nosso conhecimento, nenhum estudo se dedicou a resolver estes dois problemas conjuntamente. Nesta dissertação, propomos modelos lineares para os problemas de balanceamento e sequenciamento de linhas de produção multi-modelo em CTDs. Para o problema de sequenciamento, limitantes inferiores e superiores e métodos heurísticos de resolução são desenvolvidos e discutidos. Testes computacionais foram efetuados e os resultados sugerem que os métodos desenvolvidos são eficientes / This study addresses the Mixed Assembly Line and Worker Assignment Balancing Problem, which generalizes two classical problems in the assembly line literature: the Mixed Assembly Line Balancing Problem (MALBP) and the Assembly Line Worker Assignment and Balacing Problem (ALWABP). The MALBP has been considered particularly important in the last two decades, when, in the context of more competitive scenarios, there is a growing need of producing customized products in large scale. On the other hand, the ALWABP is of interest in Sheltered Work centers for the Disabled (SWD). In this situation, we must consider each worker individual abilities, which results in task duration times that are dependent on the workers selected for their execution. To the best of our knowledge, there has been no effort to solve these problems jointly. We propose linear models for both balancing and sequencing multimodels assembly lines commonly found in SWD. Lower and upper bounds and also heuristic methods are proposed and discussed for the sequencing problem. The results obtained by computational experiments suggest the heuristic methods can efficiently solve the MALWABP

Este trabalho lida com o problema de balanceamento e sequenciamento de linhas de produção multi-modelo com trabalhadores deficientes, uma generalização de dois importantes problemas da literatura de linhas de produção: o Problema de Balanceamento de Linhas de Produção Multi-Modelo (MALBP) e o Problema de Balanceamento e Designação de Trabalhadores em Linhas de Produção (ALWABP). O MALBP tem sido particularmente importante nas últimas décadas, onde, em um cenário de maior competividade, cresce a necessidade de produção em larga escala de produtos customizados. O ALWABP, por sua vez, é de grande importância em Centros de Trabalhadores com Deficiências (CTDs), onde é necessário considerar as competências individuais de cada trabalhador, que se revelam nos diferentes tempos de execução de uma tarefa, segundo o trabalhador escolhido. Ao nosso conhecimento, nenhum estudo se dedicou a resolver estes dois problemas conjuntamente. Nesta dissertação, propomos modelos lineares para os problemas de balanceamento e sequenciamento de linhas de produção multi-modelo em CTDs. Para o problema de sequenciamento, limitantes inferiores e superiores e métodos heurísticos de resolução são desenvolvidos e discutidos. Testes computacionais foram efetuados e os resultados sugerem que os métodos desenvolvidos são eficientes / This study addresses the Mixed Assembly Line and Worker Assignment Balancing Problem, which generalizes two classical problems in the assembly line literature: the Mixed Assembly Line Balancing Problem (MALBP) and the Assembly Line Worker Assignment and Balacing Problem (ALWABP). The MALBP has been considered particularly important in the last two decades, when, in the context of more competitive scenarios, there is a growing need of producing customized products in large scale. On the other hand, the ALWABP is of interest in Sheltered Work centers for the Disabled (SWD). In this situation, we must consider each worker individual abilities, which results in task duration times that are dependent on the workers selected for their execution. To the best of our knowledge, there has been no effort to solve these problems jointly. We propose linear models for both balancing and sequencing multimodels assembly lines commonly found in SWD. Lower and upper bounds and also heuristic methods are proposed and discussed for the sequencing problem. The results obtained by computational experiments suggest the heuristic methods can efficiently solve the MALWABP

nÃo hà / A resoluÃÃo de um Problema de Sequenciamento sempre à uma operaÃÃo que demanda grandes recursos, devido ao grande volume de dados inerentes a formulaÃÃo do problema. O uso bem sucedido do Algoritmo GenÃtico quando aplicado ao Problema de Sequenciamento ClÃssico deu-se atravÃs dos experimentos computacionais encontrados na literatura. O objetivo geral deste trabalho à relacionar as similaridades do Problema de Sequenciamento ClÃssico como um Problema do Caixeiro Viajante e resolvÃ-lo utilizando a metaheurÃstica Algoritmo GenÃtico. Foram realizados experimentos computacionais utilizando as instÃncias da OR-Library (Beasley, 1990), conjunto de dados de Taillard (1993). A anÃlise das soluÃÃes obtidas por operadores genÃticos foram realizadas, com o intuito de mostrar a evoluÃÃo da busca. O mÃtodo proposto foi comparado com outros mÃtodos discretos, onde constata-se o bom desempenho do Algoritmo GenÃtico, apresentando melhores resultados em 69 das 90 instÃncias testadas. / The resolution of a Flow Shop Problem is always an operation which requires great resources, due to the large volume of data inherent in the problem formulation. The successful use of Genetic Algorithm when applied to the Classic FSP took place through computational experiments found in the literature. The aim of this work is to relate the similarities of the Classic Scheduling Problem as a Traveling Salesman Problem (TSP) and solve it using the Genetic Algorithm metaheuristic. Computational experiments were performed using the OR - Library instances (Beasley, 1990), dataset of Taillard (1993). The analysis of the solutions obtained by genetic operators were carried out in order to show the progress of the search. The proposed method was compared with other discrete methods where there is evidence of the good performance of Genetic Algorithm

The less-than-truckload (LTL) transportation industry is highly competitive with low profit margins. Carriers in this industry strive to reduce costs and improve customer service to remain profitable. LTL carriers rely on a network of hubs and service centers to transfer freight. A hub is typically a cross docking terminal in which shipments from inbound trailers are unloaded and reassigned and consolidated onto outbound trailers going to the correct destinations. Freight handling in a hub is labor intensive, and workers must quickly transfer freight during a short time period to support customer service levels. Reducing shipment transfer time in hubs offers the opportunity to reduce labor costs, improve customer service, and increase competitive advantages for carriers. This research focuses on improving the efficiency of hub operations in order to decrease the handling costs and increase service levels for LTL carriers. Specifically, the following two decision problems are investigated: (1) assigning trailers to dock doors to minimize the total time required to transfer shipments from inbound trailers to destination trailers and (2) sequencing unloading and loading of freight to minimize the time required by dock employees. The trailer-to-door assignment problem is modeled as a Quadratic Assignment Problem (QAP). Both semi-permanent and dynamic layouts for the trailer-to-door assignment problem are evaluated. Improvement based heuristics, including pair-wise exchange, simulated annealing, and genetic algorithms, are explored to solve the trailer-to-door assignment problem. The freight sequencing problem is modeled as a Rural Postman Problem (RPP). A Balance and Connect Algorithm (BCA) and an Assign First and Route Second Algorithm (AFRSA) are investigated and compared to Balanced Trailer-at-a-Time (BTAAT), Balanced Trailer-at-a-Time with Offloading (BTAATWO), and Nearest Neighbor (NN). The heuristics are evaluated using data from two LTL carriers. For these data sets, both the total travel distance and the transfer time of hub operations are reduced using a dynamic layout with efficient freight sequencing approaches, such as the Balance and Connect Algorithm (BCA), the Balanced Trailer-at-a-Time with Offloading (BTAATWO), and the Nearest Neighbor (NN). Specifically, with a dynamic layout, the BCA reduces travel distance by 10% to 27% over BTAAT and reduces the transfer time by 17% to 68% over BTAAT. A simulation study is also conducted for hub operations in a dynamic and stochastic environment. The solutions from the door assignment and freight sequencing approaches are evaluated in a simulation model to determine their effectiveness in this environment. The simulation results further demonstrate that the performance measures of hub operations are improved using a dynamic layout and efficient freight sequencing approaches. The main contributions of this research are the integer programming models developed for the freight sequencing problem (FSP), based on the Rural Postman Problem (RPP). This is the first known application of the RPP for the FSP. Efficient heuristics are developed for the FSP for a single worker and for multiple workers. These heuristics are analyzed and compared to previous research using industry data. / Ph. D.