The group scheduling problem commonly arises in cellular manufacturing systems, where parts are grouped into part families. It is characterized by a sequencing task on two levels: on the one hand, a sequence of jobs within each part family has to be identified while, on the other hand, a family sequence has to be determined. In order to solve this NP-hard problem usually heuristic solution approaches are used. In this thesis different aspects of group scheduling are discussed and problem specific heuristics are developed to solve group scheduling problems efficiently. Thereby, particularly characteristic properties of flowshop group scheduling problems, such as the structure of a group schedule or missing operations, are identified and exploited. In a simulation study for job shop manufacturing cells several novel dispatching rules are analyzed. Furthermore, a comprehensive review of the existing group scheduling literature is presented, identifying fruitful directions for future research.

A flexible workforce or a versatile machine is employed to perform various types of operations. Often these resources are associated with setups. Whenever a worker or machine switches from processing one type of operation to another a setup time may be required although several operations of a same type can be processed in succession after a single setup. The presence of setups gives rise to the problem of choosing batch sizes that are neither too large nor too small. In the last one and a half decade, many researchers have addressed the problem of scheduling with batching. A majority of articles assumes that there is only one type of scarce resource, which is typically machine. Often there can be two scarce resources such as a worker and a machine or a machine and a tool. We propose a resource constrained scheduling model with a single operator and two or more machines. Whenever the operator changes machine, a setup time is required that may be sequence dependent or sequence independent. We consider the two cases of an open shop and a flow shop. In the open shop case, the order in which a job visits the machines is unrestricted. In the flow shop case, every job must visit the machines in the same order. We consider various scheduling objectives. For variable number of machines, many cases are intractable. We discuss some dominance properties that narrow down the search for an optimal schedule. We present a dynamic programming approach which solves a large number of cases. The running time of the dynamic program is polynomial for a fixed number of machines. For the case of two machines, we show that the dominance properties have a nice interpretation. We develop some algorithms and justify their use by establishing running times, comparing the running times with those of the existing algorithms, and testing the performance of the algorithms.

Este trabalho dedica-se ao problema de programação em flow shop permutacional com tempos de setup separados dos tempos de processamento e independentes da seqüência de execução das tarefas com o objetivo de minimizar a duração total da programação (Makespan). Por intermédio de investigações realizadas sobre as características estruturais do problema de programação e sua solução, uma propriedade deste problema é apresentada. Esta propriedade, denominada \"Propriedade LBY\", considerando quaisquer duas tarefas adjacentes Ju e Jv (Ju imediatamente precede Jv) independentemente de suas posições na seqüência de tarefas, fornece, um limitante inferior do tempo de espera para a tarefa Jv entre o fim do seu processamento na máquina Mk e o início do seu processamento na máquina seguinte. Dois novos métodos heurísticos são desenvolvidos, com base na propriedade apresentada e no procedimento de inserção de tarefas dos conhecidos métodos N&M e NEH: um construtivo, denominado BMc; e, um melhorativo, denominado BMm. Os métodos heurísticos propostos são comparados com os métodos heurísticos melhorativos de Cao; Bedworth (1992) e Rajendran; Ziegler (1997), através de um grande número de problemas gerados aleatoriamente. Os tempos de processamento são distribuídos no intervalo [1, 99] e os tempos de setup nos intervalos de [1, 49], [1, 99], [51, 149] e [101, 199]. Os métodos são avaliados quanto à porcentagem de sucesso em obter a melhor solução, ao desvio relativo médio e o tempo médio de computação. Os resultados da experimentação computacional mostram a qualidade do método construtivo BMc e a melhor performance do método melhorativo BMm. Estes resultados são apresentados e discutidos. / This work addresses the permutation flow shop scheduling problem with separated, non-batch, and sequence-independent setup times with the objective of minimizing the total time to complete the schedule (Makespan). Following an investigation of problem structural characteristics and your solution a property of this scheduling problem is presented. This property, denoted by \"Property LBY\", given any two adjacent jobs Ju e Jv (Ju immediately precedes Jv), regardless of their position in the sequence of jobs, provides an lower bound of the waiting time for job Jv between the end of its operations on the machine Mk and the beginning on machine M(k+1). Two news heuristics methods are development, on the basis of the presented property and in the job insertion procedure of the known methods named N&M and NEH: one constructive, denote by BMc; and, one improvement, denote by BMm. The proposed heuristics methods are compared with the improvement heuristics methods of Cao; Bedworth (1992) and Rajendran; Ziegler (1997), by a large number of randomly generated problems. The processing time are sampled from a distribution ranging from [1, 99] and, the setup times are sampled from distributions ranging from [1, 49], [1, 99], [51, 149] and [101, 199]. The methods are evaluated by the percentage of success in find the best solution, the average relative deviation and the average computation time. The results of the computational investigation show the quality of the constructive heuristic method BMc and that the improvement heuristic method BMc outperforms all others. These results are presented and discussed.

Les travaux présentés dans cette thèse portent sur l’ordonnancement d’applications multi-tâches linéaires de type workflow sur des plateformes distribuées. La particularité du système étudié est que le nombre de machines composant la plateforme est plus petit que le nombre de tâches à effectuer. Dans ce cas les machines sont supposées être capables d’effectuer toutes les tâches de l’application moyennant une reconfiguration, sachant que toute reconfiguration demande un temps donné dépendant ou non des tâches. Le problème posé est de maximiser le débit de l’application,c’est à dire le nombre moyen de sorties par unité de temps, ou de minimiser la période, c’est à dire le temps moyen entre deux sorties. Par conséquent le problème se décompose en deux sous problèmes: l’assignation des tâches sur les machines de la plateforme (une ou plusieurs tâches par machine), et l’ordonnancement de ces tâches au sein d’une même machine étant donné les temps de reconfiguration. Pour ce faire la plateforme dispose d’espaces appelés buffers, allouables ou imposés, pour stocker des résultats de production temporaires et ainsi éviter d’avoir à reconfigurer les machines après chaque tâche. Si les buffers ne sont pas pré-affectés nous devons également résoudre le problème de l’allocation de l’espace disponible en buffers afin d’optimiser l’exécution de l’ordonnancement au sein de chaque machine. Ce document est une étude exhaustive des différents problèmes associés à l’hétérogénéité de l’application ; en effet si la résolution des problèmes est triviale avec des temps de reconfiguration et des buffers homogènes, elle devient bien plus complexe si ceux-ci sont hétérogènes. Nous proposons ainsi d’étudier nos trois problèmes majeurs pour différents degrés d’hétérogénéité de l’application. Nous proposons des heuristiques pour traiter ces problèmes lorsqu’il n’est pas possible de trouver une solution algorithmique optimale. / In this document we tackle scheduling problems of multitask linear workflow applications ondistributed platforms. In our particular problem the number of available machines on the platformis lower than the number of stages within the pipeline. The machines are then assumed to be able toperform any kind of task on the application given the appropriate reconfiguration (or setup), the catchbeing that any reconfiguration is time consuming. The problem that we try to solve is to maximizethe throughput of such applications, i.e., the mean amount of outputs per unit of time, or to minimizeits period, i.e., the average time between two outputs. As a result this problem is split into two subproblems:mapping tasks onto different machines of the platform (most machines will likely handleseveral tasks), and find an optimal schedule within a machine while taking setup times into account.To solve this we introduce buffers, which are spaces available for each machine to store temporaryproduction results and avoid reconfiguring after each task execution, and which may or may notbe already allocated for each stage. If those buffers are not already allocated to each task then athird problem must be solved to properly allocate the available space onto each buffer, as differentbuffer configurations have a huge impact on the scheduling of a machine. This document presentsan exhaustive coverage of the different problems that are associated with the heterogeneity of theapplication; the problems with homogeneous buffer capacities and setup times are rather simple tosolve, but they get a lot more complex as heterogeneity increases. We study the three main subproblemsfor each heterogeneity combination, and offer heuristic solution to solve them when anoptimal solution cannot be reasonably found.

Este trabalho aborda o problema de programação da produção em um flexible flow line com tempos de setup. De acordo com a literatura, este ambiente pode ser considerado como um caso especial do Flow Shop com múltiplas máquinas, onde as tarefas podem saltar estágios. Neste estudo, foram analisados dois problemas: o primeiro, com tempos de setup independentes da sequência, e o segundo, com setup dependente da sequência de tarefas. Além disso, o setup das máquinas para as tarefas pode ser antecipado ou não. No primeiro caso, as máquinas de um estágio podem ser preparadas para o processamento de uma tarefa antes do seu término no estágio anterior. Se o setup não pode ser antecipado, a tarefa deve esperar o seu término no estágio de produção anterior. Este ambiente produtivo pode ser encontrado em um vasto número de indústrias tais como química, eletrônica, automotiva e têxtil. A medida de desempenho dos problemas é a duração total da programação (makespan). Este é um critério apropriado para sistemas de produção com grandes cargas de trabalho e em que a utilização dos recursos produtivos em longo prazo deve ser otimizada. O exame da literatura mostrou que há poucos estudos abordando a programação em flexible flow line. Considerando este aspecto, este trabalho apresenta heurísticas construtivas originais para a obtenção de programações apropriadas ao problema mencionado. Uma extensiva experimentação computacional foi executada para avaliar o desempenho relativo das heurísticas. Os resultados experimentais foram analisados e discutidos. / This work addresses the job scheduling on a flexible flow line with separate setup times. According to the literature, this scheduling problem can be considered as a special case of the Flow Shop with multiple machines, where the jobs may skip stages. Two modeled problems have been studied. In the first scheduling problem the setup times are sequence independent, and in the second one these times are sequence dependent. Moreover, the machine setup task can be either anticipatory or non-anticipatory. In the first case, a k-stage machine may be prepared for a job processing before its completion on the k-1 production stage. Otherwise, the setup task must wait for the job completion on the former production stage. This production environment can be found in a number of industries such as chemicals, electronics, automotive, and textiles. The performance measure of the production schedules is the makespan, that is, the total time to complete the schedule. This is an appropriate performance criterion for production systems with large workloads, and where the utilization of productive resources in the long term should be optimized. The literature examination has shown that there is a small number of studies dealing with flexible flow line scheduling. Having this in mind, this work introduces original constructive heuristics in order to obtain suitable schedules for the aforementioned scheduling problem. An extensive computational experience has been carried out in order to evaluate the relative performance of the heuristics. Experimental results are discussed.

A flexible workforce or a versatile machine is employed to perform various types of operations. Often these resources are associated with setups. Whenever a worker or machine switches from processing one type of operation to another a setup time may be required although several operations of a same type can be processed in succession after a single setup. The presence of setups gives rise to the problem of choosing batch sizes that are neither too large nor too small. In the last one and a half decade, many researchers have addressed the problem of scheduling with batching. A majority of articles assumes that there is only one type of scarce resource, which is typically machine. Often there can be two scarce resources such as a worker and a machine or a machine and a tool. We propose a resource constrained scheduling model with a single operator and two or more machines. Whenever the operator changes machine, a setup time is required that may be sequence dependent or sequence independent. We consider the two cases of an open shop and a flow shop. In the open shop case, the order in which a job visits the machines is unrestricted. In the flow shop case, every job must visit the machines in the same order. We consider various scheduling objectives. For variable number of machines, many cases are intractable. We discuss some dominance properties that narrow down the search for an optimal schedule. We present a dynamic programming approach which solves a large number of cases. The running time of the dynamic program is polynomial for a fixed number of machines. For the case of two machines, we show that the dominance properties have a nice interpretation. We develop some algorithms and justify their use by establishing running times, comparing the running times with those of the existing algorithms, and testing the performance of the algorithms.

The focuses of this dissertation are problems of batch production scheduling problems for perishable products with setup times, with the main applications in answering production planning problems faced by manufacturers of perishable products, such as beers, vaccines and yoghurts. The benefits of effective production plans can help companies reduce their total costs substantially to gain the competitive advantages without reduction of the service level in a globalize economy. We develop concepts and methodologies that are applied in two fundamental problems: (i) the batch production scheduling problem for perishable products with sequence-independent setup times (BPP-SI) and (ii) the batch production scheduling problem for perishable products with sequence-dependent setup times (BPP-SD). The problem is that given a set of forecast demand for perishables products to be produced by a set of parallel machines in the single stage of batch production, with each product having fixed shelf-life times and each machine requiring setup times before producing a batch of product, find the master production schedule which minimizes total cost over a specified time horizon. We present the new models for both problems by formulating them as a Mixed Integer Program (MIP) on the discrete time. Computational studies in BPP-SI and BPP-SD for industrial problems are presented. In order to efficiently solve the large BPP-SI problems in practice, we develop the five efficient heuristics. The extensive computational results show that the developed heuristics can obtain the good solution for the very large problem size and require very short amount of computational time.

A concorrência nos mercados mundiais impõe a necessidade de aumento da competitividade das empresas que desejam assumir posições de liderança nos segmentos em que atuam. Neste ínterim, a programação de tarefas contribui para que as empresas promovam a eficiente utilização dos recursos produtivos visando a realização de seus objetivos estratégicos. Esta dissertação enfoca a programação de tarefas em máquinas paralelas não-relacionadas e com tempos de setup dependentes da sequência de processamento. Primeiramente é abordado o objetivo de minimização do atraso total e do tempo total para a conclusão de um conjunto de tarefas, através de uma heurística de três etapas que (i) ordena as tarefas pelo WSPT (Weighted Shortest Processing Time), (ii) aloca as tarefas às máquinas e (iii) aprimora a solução proposta pela etapa (ii) através de Tabu Search. Quando aplicada em um ambiente de manufatura real composto por duas máquinas paralelas não-relacionadas no processo de metalização de filmes plásticos em alto vácuo, a heurística resulta em um desvio de 1,1% para o tempo total de processamento das tarefas e 4,6% para o atraso total, em comparação ao resultado ótimo obtido por enumeração. Na sequência, o objetivo passa a ser a minimização simultânea do atraso e do adiantamento das tarefas através de uma heurística de três etapas que (i) caracteriza o conjunto de tarefas por um conjunto de métricas, (ii) aloca as tarefas às máquinas através de uma versão modificada do ATCS (Apparent Tardiness Cost with Setup) de Lee e Pinedo (1997), e (iii) aprimora a solução final com Tabu Search. A aplicação em dados reais resulta em 14% de desvio em relação à solução ótima obtida por enumeração. Quando aplicada em cenários com data de entrega, tempos de processamento e setup simulados, a heurística resulta em desvio médio de 18% da solução ótima gerada por enumeração para pelo menos 70% das simulações. / The competition in worldwide markets lead the companies to increase the competitiveness in order to take leading positions in their industries. In this sense, scheduling plays an important role leading the companies to reach their strategic goals through efficient utilization of manufacturing resources. This dissertation focuses on the scheduling unrelated parallel machines with sequence dependent setup times. First goal is to minimize the completion time and total weighted tardiness, through a three phase heuristic which (i) sort the jobs with WSPT, (ii) allocate the jobs to the machines and (iii) improve final solution with Tabu Search. Once applied to a real manufacturing environment composed by two unrelated parallel machines, in high vacuum plastic films metallisation process, the heuristic results in 1.1% of deviation from total weighted completion time and 4.6% of deviation from weighted tardiness, in relation to the optimal solution obtained from total enumeration. Next goal is the simultaneous minimization of weighted earliness and tardiness, through a three phase heuristic which (i) characterize the jobs, (ii) allocate the jobs to the machines with a modified version of Lee and Pinedo’s (1997) ATCS and (iii) improve final solution with Tabu Search. The application in real data results in 14% of deviation from the optimal solution obtained by enumeration. When applied to simulated scenarios of due date, processing and setup time, the heuristic results in average deviation of 18% from optimal solution obtained by enumeration to at least 70% of the simulations.

A concorrência nos mercados mundiais impõe a necessidade de aumento da competitividade das empresas que desejam assumir posições de liderança nos segmentos em que atuam. Neste ínterim, a programação de tarefas contribui para que as empresas promovam a eficiente utilização dos recursos produtivos visando a realização de seus objetivos estratégicos. Esta dissertação enfoca a programação de tarefas em máquinas paralelas não-relacionadas e com tempos de setup dependentes da sequência de processamento. Primeiramente é abordado o objetivo de minimização do atraso total e do tempo total para a conclusão de um conjunto de tarefas, através de uma heurística de três etapas que (i) ordena as tarefas pelo WSPT (Weighted Shortest Processing Time), (ii) aloca as tarefas às máquinas e (iii) aprimora a solução proposta pela etapa (ii) através de Tabu Search. Quando aplicada em um ambiente de manufatura real composto por duas máquinas paralelas não-relacionadas no processo de metalização de filmes plásticos em alto vácuo, a heurística resulta em um desvio de 1,1% para o tempo total de processamento das tarefas e 4,6% para o atraso total, em comparação ao resultado ótimo obtido por enumeração. Na sequência, o objetivo passa a ser a minimização simultânea do atraso e do adiantamento das tarefas através de uma heurística de três etapas que (i) caracteriza o conjunto de tarefas por um conjunto de métricas, (ii) aloca as tarefas às máquinas através de uma versão modificada do ATCS (Apparent Tardiness Cost with Setup) de Lee e Pinedo (1997), e (iii) aprimora a solução final com Tabu Search. A aplicação em dados reais resulta em 14% de desvio em relação à solução ótima obtida por enumeração. Quando aplicada em cenários com data de entrega, tempos de processamento e setup simulados, a heurística resulta em desvio médio de 18% da solução ótima gerada por enumeração para pelo menos 70% das simulações. / The competition in worldwide markets lead the companies to increase the competitiveness in order to take leading positions in their industries. In this sense, scheduling plays an important role leading the companies to reach their strategic goals through efficient utilization of manufacturing resources. This dissertation focuses on the scheduling unrelated parallel machines with sequence dependent setup times. First goal is to minimize the completion time and total weighted tardiness, through a three phase heuristic which (i) sort the jobs with WSPT, (ii) allocate the jobs to the machines and (iii) improve final solution with Tabu Search. Once applied to a real manufacturing environment composed by two unrelated parallel machines, in high vacuum plastic films metallisation process, the heuristic results in 1.1% of deviation from total weighted completion time and 4.6% of deviation from weighted tardiness, in relation to the optimal solution obtained from total enumeration. Next goal is the simultaneous minimization of weighted earliness and tardiness, through a three phase heuristic which (i) characterize the jobs, (ii) allocate the jobs to the machines with a modified version of Lee and Pinedo’s (1997) ATCS and (iii) improve final solution with Tabu Search. The application in real data results in 14% of deviation from the optimal solution obtained by enumeration. When applied to simulated scenarios of due date, processing and setup time, the heuristic results in average deviation of 18% from optimal solution obtained by enumeration to at least 70% of the simulations.

Este trabalho aborda o problema de programação da produção em um flexible flow line com tempos de setup. De acordo com a literatura, este ambiente pode ser considerado como um caso especial do Flow Shop com múltiplas máquinas, onde as tarefas podem saltar estágios. Neste estudo, foram analisados dois problemas: o primeiro, com tempos de setup independentes da sequência, e o segundo, com setup dependente da sequência de tarefas. Além disso, o setup das máquinas para as tarefas pode ser antecipado ou não. No primeiro caso, as máquinas de um estágio podem ser preparadas para o processamento de uma tarefa antes do seu término no estágio anterior. Se o setup não pode ser antecipado, a tarefa deve esperar o seu término no estágio de produção anterior. Este ambiente produtivo pode ser encontrado em um vasto número de indústrias tais como química, eletrônica, automotiva e têxtil. A medida de desempenho dos problemas é a duração total da programação (makespan). Este é um critério apropriado para sistemas de produção com grandes cargas de trabalho e em que a utilização dos recursos produtivos em longo prazo deve ser otimizada. O exame da literatura mostrou que há poucos estudos abordando a programação em flexible flow line. Considerando este aspecto, este trabalho apresenta heurísticas construtivas originais para a obtenção de programações apropriadas ao problema mencionado. Uma extensiva experimentação computacional foi executada para avaliar o desempenho relativo das heurísticas. Os resultados experimentais foram analisados e discutidos. / This work addresses the job scheduling on a flexible flow line with separate setup times. According to the literature, this scheduling problem can be considered as a special case of the Flow Shop with multiple machines, where the jobs may skip stages. Two modeled problems have been studied. In the first scheduling problem the setup times are sequence independent, and in the second one these times are sequence dependent. Moreover, the machine setup task can be either anticipatory or non-anticipatory. In the first case, a k-stage machine may be prepared for a job processing before its completion on the k-1 production stage. Otherwise, the setup task must wait for the job completion on the former production stage. This production environment can be found in a number of industries such as chemicals, electronics, automotive, and textiles. The performance measure of the production schedules is the makespan, that is, the total time to complete the schedule. This is an appropriate performance criterion for production systems with large workloads, and where the utilization of productive resources in the long term should be optimized. The literature examination has shown that there is a small number of studies dealing with flexible flow line scheduling. Having this in mind, this work introduces original constructive heuristics in order to obtain suitable schedules for the aforementioned scheduling problem. An extensive computational experience has been carried out in order to evaluate the relative performance of the heuristics. Experimental results are discussed.