The diploma thesis deals with linear integer optimization in production logistics via mathematical programming. This tool is used for optimization of the time production schedule with a number of various jobs performed by a company with limited resources. The thesis solves the problem in conjunction with TOSHULIN, a.s. company, which is interested in solving the problem. As a result is the software implementation in which Gantt chart is created as its output.

This thesis examines the problem of identifying patterns in process event logs that are correlated with binary events that are undetected until the end of the process. Specifically, we consider the task of identifying patterns in a machine shop manufacturing process that are correlated with product defect. We introduce a pattern mining algorithm based on Apriori to identify frequent patterns, and use binary correlation measures to identify patterns associated with elevated defect rate. We design a simulation model to generate synthetic datasets to test our algorithm. We compare the effectiveness of different correlation measures, target pattern complexities, and sample sizes with and without knowledge of the underlying process. We show that knowledge of the underlying process helps in identifying the pattern that is associated with defects. We also develop a decision support tool based on p-value simulation to help managers identify sources of error in real-life settings. Finally, we apply our method to real world data and extract useful information from the data to help plant managers make decisions related to investments and workforce planning. This thesis also explores the problem of predicting the defect probability given an ordered list of events and its defect status. We develop a supervised learning model using the frequency of patterns deduced from the event log as the feature set. We discuss the challenges faced in this approach and conclude that random forest algorithm performs better than other methods. We apply this approach to a real world case study and discuss the applications in the machine shop. Finally, the thesis explores the order-bidding process in the machine shop industry, and proposes an optimization-based model to maximize the profit of the machine shop. Through a case study example, we show the advantages of using the defect probability in the proposed optimization model to determine the machine-worker schedule to execute job orders in a machine shop.

Made available in DSpace on 2014-06-11T19:26:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-01-30Bitstream added on 2014-06-13T20:55:42Z : No. of bitstreams: 1 lopes_am_me_sjrp.pdf: 648692 bytes, checksum: 6aa3a670ac391b9033fe7de1566f1648 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Este trabalho trata do problema de corte de estoque unidimensional inteiro, que consiste em cortar um conjunto de objetos disponíveis em estoque para a produção de itens menores demandados, de tal forma que se otimize uma ou mais funções objetivos. Foi estudado o caso em que existe apenas um tipo de objeto em estoque em quantidades suficiente para atender a demanda. Três adaptações de um método heurístico baseadas nos conceitos dos algoritmos evolutivos multiobjetivo são propostas para resolver o problema considerando duas funções objetivo conflitantes, a minimização do número de objetos cortados e a minimização do número de diferentes padrões de corte. As adaptações utilizam as idéias presentes no método da Soma Ponderada, no Vector Evaluated Genetic Algorithm e no Multiple Objective Genetic Algorithm. Estas heurísticas são analisadas resolvendo-se instâncias geradas aleatoriamente. / This work deals with the one-dimensional integer cutting stock problem, which consist of cutting a set of available objects in stock in order to produce ordered smaller items in such a way as to optimize one or more objective functions. On the case studied there is just one type of object in stock available in sufficient quantity to satisfy the demand. Three adaptations of a heuristic method based on the multi-objective evolutionary algorithms concepts are proposed to solve the problem considering two conflicting objective functions, the minimization of the number of objects to be cut and the minimization of the number of different cutting patterns. The adaptations consider the ideas from the Weighted Sum method, the Vector Evaluated Genetic Algorithm and the Multiple Objective Genetic Algorithm. These heuristics are analyzed by solving randomly generated instances.

This thesis deals with modelling diffenrent types of production lines. Modeling is done by the mathematical programming and simulation methods. Optimization related computations are mostly implemented in program GAMS. Simulation is realized by using program Matlab/SimEvents. The results are presented by the Gantt diagrams.

This report aimed to develop algorithms for solving the optimization problem of matchingbuy and sell orders in call auctions while minimizing the number of transactions. The developed algorithms were evaluated based on their execution time and solution accuracy.The study found that the problem was more difficult to solve than initially anticipated, and commercial solvers were inadequate for the task. The data’s characteristics werecritical to the algorithms’ performance, and the lack of specifications for instruments andexchange posed a challenge. The algorithms were tested on a broad range of datasets with different characteristics, as well as real trades of stocks from the Stockholm Stock Exchange. Evaluating the best-performing algorithm became a trade-off between time and accuracy, where the quickest algorithm did not have the highest solution accuracy. Therefore, the importance of these factors should be considered before deciding which algorithm to implement. Eight algorithms were evaluated: four greedy algorithms and four clusteralgorithms capable of identifying 2-1 and 3-1 matches. If execution time is the single most crucial factor, the Unsorted Greedy Algorithm should be considered. However, if accuracyi s a priority, the Cluster 3-1 & 1-3 Algorithm should be considered, even though it takes longer to find a solution. Ultimately, the report concluded that while no single algorithm can be definitively la-beled as the best, the Cluster 2-1 Algorithm strikes the most effective balance between execution time and solution accuracy, while also remaining relatively stable in perfor-mance for all test cases. The recommendation was based on the fact that the Cluster 2-1 Algorithm proved to be the quickest of the developed cluster algorithms, and that cluster algorithms were able to find the best solutions for all tested data sets. This study successfully addressed its purpose by developing eight algorithms that solved the given problem and suggested an appropriate algorithm that strikes a balance between execution time and solution quality.

A complexidade de alguns sistemas biotecnológicos impossibilita seu estudo sem o uso de técnicas de programação matemática avançadas. A quantificação de fluxos metabólicos e a síntese e projeto ótimos de plantas multiproduto são problemas com esta característica, abordados na presente tese. A quantificação de fluxos metabólicos empregando balanços de marcações é representada como um problema de otimização não-linear, o qual se resolve através da minimização da diferença entre as medidas experimentais e as predições do modelo da rede metabólica. Este problema surge da necessidade de se caracterizar o metabolismo mediante a estimação das velocidades das reações bioquímicas. O modelo matemático para problemas deste tipo é composto basicamente por balanços de metabólitos e de isótopos; os primeiros são lineares, enquanto os segundos introduzem não-linearidades ao problema e, neste trabalho, são modelados mediante uma modificação da técnica de matrizes de mapeamento de átomos. Para quantificar os fluxos metabólicos considerando a existência de ótimos locais, desenvolveu-se um algoritmo branch & bound espacial, no qual a busca global é feita mediante a divisão da região de busca (branching) e a geração de seqüências de limites (bounding) que convergem para a solução global. Como estudo de caso, estimaram-se os fluxos no metabolismo central de Saccharomyces cerevisiae. Os resultados confirmam a existência de soluções locais e a necessidade de desenvolver uma estratégia de busca global; a solução global obtida apresenta semelhanças, nos fluxos centrais, com a melhor solução obtida por um algoritmo evolucionário. Quanto aos problemas de síntese e projeto de sistemas biotecnológicos multiproduto, As abordagens mais empregadas para resolve-los são a definição e dimensionamento seqüencial das operações unitárias, e a fixação dos parâmetros de dimensionamento e de estimação do tempo de operação (com valores obtidos em laboratório ou planta piloto); porém ambas abordagens fornecem soluções subótimas. Por outro lado, a solução simultânea da síntese e projeto de sistemas biotecnológicos multiproduto gera modelos misto-inteiros não-lineares (MINLP) de grande porte, devido à combinação das decisões, ligadas à existência de alternativas no processo, com as restrições não-lineares geradas dos modelos das operações. Como estudo de caso considera-se uma planta para produção de insulina, vacina para hepatite B, ativador de plasminogênio tecidual (tissue plasminogen activator) e superóxido dismutase, mediante três hospedeiros diferentes: levedura (S. cerevisiae) com expressão extra ou intracelular, Escherichia coli e células de mamíferos. O projeto deve satisfazer a meta de produção para cada produto, minimizando os custos de capital e selecionando os hospedeiros, as operações e o arranjo dos equipamentos em cada estágio. Os resultados obtidos mostram que a formulação das decisões por abordagem big-M permite resolver o modelo MINLP gerado e que a consideração de múltiplos produtos com seqüências e condições de processamento diferentes gera grande ociosidade nos equipamentos e aumenta o custo total do projeto. Para o estudo de caso observou-se que a alocação de tanques intermediários tem um efeito limitado na diminuição do custo do projeto, porém a implementação simultânea da flexibilização do scheduling, do projeto de equipamentos auxiliares e tanques intermediários permite obter projetos satisfatórios. / The complexity of biotechnological systems does not allow their study without the use of advanced mathematical programming techniques. Metabolic flux quantification and optimal synthesis and design of multiproduct plants are problems with this characteristic, and are addressed in this thesis. The metabolic flux quantification employing labeling balances is formulated as a nonlinear optimization problem that is solved by the minimization of the difference between experimental measurements and predictions of the metabolic network model. This problem is generated by the necessity of estimating the rates of biochemical reactions that characterize the metabolism. The mathematical model for this class of problems is composed by balances of metabolites and isotopes; the former are linear whereas the latter are nonlinear and, in this work, are modeled by a modification of the atom mapping matrix technique. A spatial branch & bound algorithm was developed to quantify the metabolic fluxes, that considers the existence of local optima; in this algorithm, the global search is developed by the division of the searching region (branching) and the generation of sequences of bounds (bounding) that converge to the global solution. As a case study, fluxes in central metabolism of Saccharomyces cerevisiae were estimated. The results confirm the existence of local solutions and the necessity of develop a global search strategy; the central fluxes in the obtained global solution are similar to those ones obtained by an evolutionary algorithm. To solve problems of synthesis and design of multiproduct biotechnological systems, the most employed approaches are the sequential selection and sizing of the unit operations, and the fixing of sizing and time parameters (employing values from laboratory or pilot plants); nevertheless, both approaches generate suboptimal solutions. On the other hand, the simultaneous solution of the synthesis and design of multiproduct biotechnological systems generates large size mixed-integer nonlinear models (MINLP), due to the combination of options into the processing with nonlinear constraints from the operation models. As case study, a plant for production of insulin, hepatitis B vaccine, tissue plasminogen activator and superoxide dismutase was considered, by three hosts: yeast (S. cerevisiae) with extra or intracellular expression, Escherichia coli and mammalian cells. The design must satisfy the production target for each product, minimizing the capital cost and considering the selection of hosts, the operations and the number of parallel units in each stage. The obtained results show that the formulation of decisions by the big-M approach allows the solution of the generated MINLP model and that consideration of several products with different processing sequences and conditions generates large idleness at the equipment and increases the total cost of the design. In the case study it was observed that the allocation of storage tanks has a limited effect on cost reduction, but the simultaneous implementation of flexible scheduling, design of auxiliary equipments and intermediate storage tanks allow the generation of satisfactory designs.

A complexidade de alguns sistemas biotecnológicos impossibilita seu estudo sem o uso de técnicas de programação matemática avançadas. A quantificação de fluxos metabólicos e a síntese e projeto ótimos de plantas multiproduto são problemas com esta característica, abordados na presente tese. A quantificação de fluxos metabólicos empregando balanços de marcações é representada como um problema de otimização não-linear, o qual se resolve através da minimização da diferença entre as medidas experimentais e as predições do modelo da rede metabólica. Este problema surge da necessidade de se caracterizar o metabolismo mediante a estimação das velocidades das reações bioquímicas. O modelo matemático para problemas deste tipo é composto basicamente por balanços de metabólitos e de isótopos; os primeiros são lineares, enquanto os segundos introduzem não-linearidades ao problema e, neste trabalho, são modelados mediante uma modificação da técnica de matrizes de mapeamento de átomos. Para quantificar os fluxos metabólicos considerando a existência de ótimos locais, desenvolveu-se um algoritmo branch & bound espacial, no qual a busca global é feita mediante a divisão da região de busca (branching) e a geração de seqüências de limites (bounding) que convergem para a solução global. Como estudo de caso, estimaram-se os fluxos no metabolismo central de Saccharomyces cerevisiae. Os resultados confirmam a existência de soluções locais e a necessidade de desenvolver uma estratégia de busca global; a solução global obtida apresenta semelhanças, nos fluxos centrais, com a melhor solução obtida por um algoritmo evolucionário. Quanto aos problemas de síntese e projeto de sistemas biotecnológicos multiproduto, As abordagens mais empregadas para resolve-los são a definição e dimensionamento seqüencial das operações unitárias, e a fixação dos parâmetros de dimensionamento e de estimação do tempo de operação (com valores obtidos em laboratório ou planta piloto); porém ambas abordagens fornecem soluções subótimas. Por outro lado, a solução simultânea da síntese e projeto de sistemas biotecnológicos multiproduto gera modelos misto-inteiros não-lineares (MINLP) de grande porte, devido à combinação das decisões, ligadas à existência de alternativas no processo, com as restrições não-lineares geradas dos modelos das operações. Como estudo de caso considera-se uma planta para produção de insulina, vacina para hepatite B, ativador de plasminogênio tecidual (tissue plasminogen activator) e superóxido dismutase, mediante três hospedeiros diferentes: levedura (S. cerevisiae) com expressão extra ou intracelular, Escherichia coli e células de mamíferos. O projeto deve satisfazer a meta de produção para cada produto, minimizando os custos de capital e selecionando os hospedeiros, as operações e o arranjo dos equipamentos em cada estágio. Os resultados obtidos mostram que a formulação das decisões por abordagem big-M permite resolver o modelo MINLP gerado e que a consideração de múltiplos produtos com seqüências e condições de processamento diferentes gera grande ociosidade nos equipamentos e aumenta o custo total do projeto. Para o estudo de caso observou-se que a alocação de tanques intermediários tem um efeito limitado na diminuição do custo do projeto, porém a implementação simultânea da flexibilização do scheduling, do projeto de equipamentos auxiliares e tanques intermediários permite obter projetos satisfatórios. / The complexity of biotechnological systems does not allow their study without the use of advanced mathematical programming techniques. Metabolic flux quantification and optimal synthesis and design of multiproduct plants are problems with this characteristic, and are addressed in this thesis. The metabolic flux quantification employing labeling balances is formulated as a nonlinear optimization problem that is solved by the minimization of the difference between experimental measurements and predictions of the metabolic network model. This problem is generated by the necessity of estimating the rates of biochemical reactions that characterize the metabolism. The mathematical model for this class of problems is composed by balances of metabolites and isotopes; the former are linear whereas the latter are nonlinear and, in this work, are modeled by a modification of the atom mapping matrix technique. A spatial branch & bound algorithm was developed to quantify the metabolic fluxes, that considers the existence of local optima; in this algorithm, the global search is developed by the division of the searching region (branching) and the generation of sequences of bounds (bounding) that converge to the global solution. As a case study, fluxes in central metabolism of Saccharomyces cerevisiae were estimated. The results confirm the existence of local solutions and the necessity of develop a global search strategy; the central fluxes in the obtained global solution are similar to those ones obtained by an evolutionary algorithm. To solve problems of synthesis and design of multiproduct biotechnological systems, the most employed approaches are the sequential selection and sizing of the unit operations, and the fixing of sizing and time parameters (employing values from laboratory or pilot plants); nevertheless, both approaches generate suboptimal solutions. On the other hand, the simultaneous solution of the synthesis and design of multiproduct biotechnological systems generates large size mixed-integer nonlinear models (MINLP), due to the combination of options into the processing with nonlinear constraints from the operation models. As case study, a plant for production of insulin, hepatitis B vaccine, tissue plasminogen activator and superoxide dismutase was considered, by three hosts: yeast (S. cerevisiae) with extra or intracellular expression, Escherichia coli and mammalian cells. The design must satisfy the production target for each product, minimizing the capital cost and considering the selection of hosts, the operations and the number of parallel units in each stage. The obtained results show that the formulation of decisions by the big-M approach allows the solution of the generated MINLP model and that consideration of several products with different processing sequences and conditions generates large idleness at the equipment and increases the total cost of the design. In the case study it was observed that the allocation of storage tanks has a limited effect on cost reduction, but the simultaneous implementation of flexible scheduling, design of auxiliary equipments and intermediate storage tanks allow the generation of satisfactory designs.

Made available in DSpace on 2014-06-11T19:26:56Z (GMT). No. of bitstreams: 0 Previous issue date: 2004-07-30Bitstream added on 2014-06-13T20:55:45Z : No. of bitstreams: 1 cavali_r_me_sjrp.pdf: 560996 bytes, checksum: 6792ea8d0dd5f26eb5250b68217a4443 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Diariamente, em indústrias de móveis, painéis retângulares de madeira são cortados em retângulos menores para a manufatura de seus produtos. Por causa da possível perda de material envolvida neste processo e de sua influência no custo dos produtos, existe a necessidade de um planejamento prþevio para a realização dos cortes. Na maioria das empresas de móveis situadas na região Noroeste do estado de São Paulo, este planejamento é feito manualmente e não é uma tarefa simples. O enfoque deste trabalho þe analisar a utilização de um sistema computacional no planejamento do corte de painéis de madeira. Esta ferramenta é capaz de resolver o problema do corte bidimensional segundo o algoritmo de dois estþagios de Gilmory e Gomore. Aspectos práticos encontrados no corte dos painéis e estratégias adotadas pelas empresas no planejamento da produção são abordados. Além disso, apresentamos os resultados de um estudo computacional com base em dados reais de uma das empresas visitadas. / In the furniture industries, the cut of rectangular plates to produce smaller rectangular pieces is an every day task. To reduce the waste of material involved in this process and its influence in the cost of the products, a previous planning for the cuts is necessary. In the majority of the furniture companies situated at Northwest region of the state of São Paulo, the generation of cutting patterns is made manually and it is not a simple task. The goal of this work is to analyze the use of a computational system in the cutting patterns generation. This computational system is able to solve the two-dimensional cutting stock problem by the 2-stage Gilmory and Gomore method. Practical aspects found in the cutting patterns generation and strategies adopted for the companies in the production planning are discussed. We also report some results of the application of the computacional system to the cutting patterns generation based on real data of one company.

Orientador: Maria do Socorro Nogueira Rangel / Banca: Robinson Hoto / Banca. Trajano Pires da Nóbrega Neto / Resumo: Diariamente, em indústrias de móveis, painéis retângulares de madeira são cortados em retângulos menores para a manufatura de seus produtos. Por causa da possível perda de material envolvida neste processo e de sua influência no custo dos produtos, existe a necessidade de um planejamento prþevio para a realização dos cortes. Na maioria das empresas de móveis situadas na região Noroeste do estado de São Paulo, este planejamento é feito manualmente e não é uma tarefa simples. O enfoque deste trabalho þe analisar a utilização de um sistema computacional no planejamento do corte de painéis de madeira. Esta ferramenta é capaz de resolver o problema do corte bidimensional segundo o algoritmo de dois estþagios de Gilmory e Gomore. Aspectos práticos encontrados no corte dos painéis e estratégias adotadas pelas empresas no planejamento da produção são abordados. Além disso, apresentamos os resultados de um estudo computacional com base em dados reais de uma das empresas visitadas. / Abstract: In the furniture industries, the cut of rectangular plates to produce smaller rectangular pieces is an every day task. To reduce the waste of material involved in this process and its influence in the cost of the products, a previous planning for the cuts is necessary. In the majority of the furniture companies situated at Northwest region of the state of São Paulo, the generation of cutting patterns is made manually and it is not a simple task. The goal of this work is to analyze the use of a computational system in the cutting patterns generation. This computational system is able to solve the two-dimensional cutting stock problem by the 2-stage Gilmory and Gomore method. Practical aspects found in the cutting patterns generation and strategies adopted for the companies in the production planning are discussed. We also report some results of the application of the computacional system to the cutting patterns generation based on real data of one company. / Mestre

L'optimisation topologique vise à concevoir une structure en recherchant la disposition optimale du matériau dans un espace de conception donné, permettant ainsi de proposer des designs optimaux innovants. Cette thèse est centrée sur l'optimisation topologique pour des problèmes de conception de structures prenant en compte des contraintes de flambage. Dans une large variété de domaines de l'ingénierie, la conception innovante de structures est cruciale. L'allègement des structures lors la phase de conception tient une place prépondérante afin de réduire les coûts de fabrication. Ainsi l'objectif est souvent la minimisation de la masse de la structure à concevoir. En ce qui concerne les contraintes, en plus des contraintes mécaniques classiques (compression, tension), il est nécessaire de prendre en compte des phénomènes dits de flambage, qui se caractérisent par une amplification des déformations de la structure et une potentielle annihilation des capacités de la structure à supporter les efforts appliqués. Dans le but d'adresser un large panel de problèmes d'optimisation topologique, nous considérons les deux types de représentation d'une structure : les structures treillis et les structures continues. Dans le cadre de structures treillis, l'objectif est de minimiser la masse en optimisant le nombre d'éléments de la structure et les dimensions des sections transversales associées à ces éléments. Nous considérons les structures constituées d'éléments poutres et nous introduisons une formulation du problème comme un problème d'optimisation non-linéaire en variables mixtes. Afin de prendre en compte des contraintes de manufacturabilité, nous proposons une fonction coût combinant la masse et la somme des seconds moments d'inertie de chaque poutre. Nous avons développé un algorithme adapté au problème d'optimisation considéré. Les résultats numériques montrent que l'approche proposée mène à des gains de masses significatifs par rapport à des approches existantes. Dans le cas des structures continues, l'optimisation topologique vise à discrétiser le domaine de conception et à déterminer les éléments de ce domaine discrétisé qui doivent être composés de matière, définissant ainsi un problème d'optimisation discret. [...] / Topology optimization aims to design a structure by seeking the optimal material layout within a given design space, thus making it possible to propose innovative optimal designs. This thesis focuses on topology optimization for structural problems taking into account buckling constraints. In a wide variety of engineering fields, innovative structural design is crucial. The lightening of structures during the design phase holds a prominent place in order to reduce manufacturing costs. Thus the goal is often the minimization of the mass of the structure to be designed. Regarding the constraints, in addition to the conventional mechanical constraints (compression, tension), it is necessary to take into account buckling phenomena which are characterized by an amplification of the deformations of the structure and a potential annihilation of the capabilities of the structure to support the applied efforts. In order to adress a wide range of topology optimization problems, we consider the two types of representation of a structure: lattice structures and continuous structures. In the framework of lattice structures, the objective is to minimize the mass by optimizing the number of elements of the structure and the dimensions of the cross sections associated to these elements. We consider structures constituted by a set of frame elements and we introduce a formulation of the problem as a mixed-integer nonlinear problem. In order to obtain a manufacturable structure, we propose a cost function combining the mass and the sum of the second moments of inertia of each frame. We developed an algorithm adapted to the considered optimization problem. The numerical results show that the proposed approach leads to significant mass gains over existing approaches. In the case of continuous structures, topology optimization aims to discretize the design domain and to determine the elements of this discretized domain that must be composed of material, thus defining a discrete optimization problem. [...]