Submitted by Fernando Souza (fernandoafsou@gmail.com) on 2017-08-16T11:42:54Z No. of bitstreams: 1 arquivototal.pdf: 2606529 bytes, checksum: e6d5e9c7169bad77fb641468b804b962 (MD5) / Made available in DSpace on 2017-08-16T11:42:54Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2606529 bytes, checksum: e6d5e9c7169bad77fb641468b804b962 (MD5) Previous issue date: 2016-07-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The problem of scheduling on a single machine, proven to be NP-hard, consists of de ning the job grouping in batches and of the sequence in which these batches will be processed on a machine. Each job is associated with a release date, a processing time, a due date, a priority level in relation to the others and a size. The machine is able to process a group of jobs (batch) simultaneously, provided that the sum of the job sizes belonging to the referred batch does not exceed the machine capacity. Each job must be processed only once and only one batch is processed at a time on the machine. In this work, we consider the objective as the minimization of total weighted tardiness, where the tardiness of a job is the di erence between its completion time and its due date, in case the job processing is nished after its due date and hence is late, or equals zero, otherwise. In the literature, this problem is usually referred to as 1jbatch; rj ; sj ; comptjPwjTj . When all jobs are available to be processed at time zero, the problem is usually represented as 1jbatch; sj ; comptjPwjTj . These problems are still poorly explored in the literature and in addition, cover a large number of variant forms. There are few studies involving the application of exact methods for solving both. Only one mathematical formulation was identi ed in the literature for these problems. Hence, four time-indexed formulations were developed to solve the aforementioned problems, one of which is capable of dealing with both problems. The results achieved by the developed models were compared between themselves and with the results of the model available in the literature. These computational results reveal that two of the proposed models obtained higher performance both in terms of quality of the solution, particularly regarding the achieved lower bounds, and in numbers of open nodes and of proven optimal solutions. / O problema de sequenciamento de lotes da produ c~ao em uma m aquina, comprovadamente tido como NP-dif cil, consiste na de ni c~ao do agrupamento de tarefas em lotes e da sequ^encia em que estes ser~ao processados em uma m aquina. Cada tarefa est a associada a uma data de libera c~ao, um tempo de processamento, uma data de entrega, um n vel de prioridade em rela c~ao as demais, e um tamanho. A m aquina e capaz de processar um conjunto de tarefas (lote) simultaneamente, contanto que a soma dos tamanhos das tarefas pertencentes ao referido lote respeite a capacidade da m aquina. Cada tarefa deve ser processada apenas uma vez e somente um lote e processado por vez na m aquina. Neste trabalho, considera-se como objetivo a minimiza c~ao do total de atrasos ponderados, onde o atraso de uma tarefa e igual ao seu tempo de t ermino menos a sua data de entrega, caso o processamento da tarefa seja nalizado ap os a sua data da entrega e, portanto, em atraso, e e igual a zero, caso contr ario. Na literatura, este problema e geralmente referenciado como 1jbatch; rj ; sj ; comptjPwjTj . Quando todas as tarefas est~ao dispon veis para serem processadas no instante de tempo zero, o problema e usualmente representado por 1jbatch; sj ; comptjPwjTj . Estes s~ao problemas ainda pouco investigados na literatura e, al em disso, abordam uma grande quantidade de variantes. Existem poucos trabalhos envolvendo a aplica c~ao de m etodos exatos para a resolu c~ao de ambos. Apenas uma formula c~ao matem atica foi identi cada na literatura para estes problemas. Dessa forma, quatro formula c~oes matem aticas com vari aveis indexadas no tempo foram desenvolvidas para resolver os problemas mencionados anteriormente, das quais uma e capaz de tratar de ambos os problemas. Os resultados alcan cados por meio dos modelos desenvolvidos foram comparados entre si e com os resultados do modelo dispon vel na literatura. Tais resultados computacionais demonstram que dois dos modelos propostos obtiveram desempenho superior tanto em termos de qualidade da solu c~ao, em especial em rela c~ao aos limites inferiores alcan cados, quanto em n umeros de n os abertos e quantidade de solu c~oes otimas comprovadas.

Informed economic decisions are made on the basis of accounting data. It is therefore crucial to have rigorous and scientific approaches for measuring, modelling and forecasting accounting numbers. Dr Falta's research was motivated by two observations. Firstly, in accounting practice, decision-making often relies on subjective quantifications and forecasts of business activities and, thus, does not account for uncertainty in a rational way. Secondly, there are some academic foundations for statistical approaches to accounting, yet none has been developed carefully enough for results to penetrate and to contribute to practitioners' needs. Dr Falta applied components of mathematics, statistics, econometrics, finance and computing to aspects of accounting and auditing. He developed an enhanced framework for scientific measurement of business process costing and recording accounting transaction data. This has enabled a better understanding of risk in accounting-based decision-making. His research is being incorporated in projects with the Royal Australian Navy and SunWater.

Le problème de gestion de projet à contraintes de ressources est un des problèmesles plus étudiés dans la littérature. Il consiste à planifier des activités soumises à desrelations de précédence, et nécessitant des ressources renouvelables. L’objectif est deminimiser la durée du projet, soit le makespan. Nous étudions le problème de gestion deprojet à contraintes de ressources. Nous nous sommes intéressées à la résolution exactedu problème. Dans la première partie de la thèse, nous élaborons une série de bornesinférieures basées sur le raisonnement énergétique et des formulations mathématiques.Les résultats montrent que les bornes proposées surpassent ceux de la littérature. Dansla deuxième partie, nous proposons des procédures par séparation et évaluation utilisantles bornes inférieures dévelopées dans la première partie. / Resource Constrained Project Scheduling Problem is one of the most studied schedulingproblems in the literature. It consists in scheduling activities, submitted to precedencerelationship, and requiring renewable resources to be processed. The objective isto minimize the project duration, i.e., the makespan. We study the Resource ConstrainedProject Scheduling Problem. We are interested on the exact resolution of the problem.In the first part of the thesis, we develop a series of lower bounds based on energeticreasoning and mathematical formulations. The computational results show that theproposed lower bounds outperform the ones of the literature. In the second part, wepropose Branch-and-Bound procedures using the lower bounds developed on the firstpart.

[pt] Empresas de exploração de petróleo e gás offshore frequentemente precisam lidar com problemas relacionados ao uso eficiente de seus recursos. Neste trabalho, abordamos um problema de programação de navios associado à logística offshore de petróleo e gás – O Problema de Programação de Embarcações do tipo Pipe-Laying support Vessel (PLSVSP). Essas embarcações são especialmente projetadas para realizar conexões de dutos entre poços de petróleo submarinos e plataformas de produção. A conexão de dutos é a última etapa a ser executada para permitir a drenagem do óleo e iniciar a produção em um poço. No PLSVSP, o objetivo é antecipar a conclusão de poços mais produtivos. O problema pode ser visto como uma variante de um problema de programação de lotes com máquinas paralelas idênticas e tempos de configuração não antecipados por família para minimizar o total weighted completion time. Nessa analogia, embarcações são as máquinas, poços são as tarefas e lotes são as viagens executadas por PLSVs, definindo quais poços devem ser conectados a cada saída do porto. Foram desenvolvidas diversas abordagens de otimização para resolver as variantes determinística e estocástica do problema. Para a variante determinística, desenvolvemos métodos híbridos e uma metaheurística capazes de melhorar as soluções desenvolvidas por formulações MIP puras e lidar com o PLSVSP. Para a variante estocástica, foi desenvolvida uma simheurística utilizando simulação de Monte Carlo incorporada, considerando incertezas nas durações das conexões e nas datas de chegada dos oleodutos no porto. Os resultados mostram uma melhora significativa no custo das soluções quando lidam com incertezas em comparação com soluções geradas por um método determinístico. O uso da simulação em uma estrutura metaheurística mostrou-se uma abordagem promissora, capaz de lidar com o problema estocástico, com pouco esforço computacional extra necessário. / [en] Offshore oil and gas exploration companies frequently need to deal with problems related to the efficient use of their resources. In this work, we address a ship scheduling problem associated with offshore oil and gas logistics – The Pipe Laying Support Vessel Scheduling Problem (PLSVSP). These vessels are specially designed to perform pipeline connections between sub-sea oil wells and production platforms. The connections are the last step to be performed to allow the oil draining, starting production in a well. The PLSVSP objective is to anticipate the completion of the most productive wells. The problem can be seen as a variant of a batch scheduling problem with identical parallel machines and non-anticipatory family setup times to minimize the total weighted completion time. In this analogy, vessels are machines, wells are jobs, and batches are voyages executed by PLSVs, defining which wells to connect each time it leaves the port. We developed several optimization approaches to solve the deterministic and stochastic variants of the problem. For the deterministic problem, we developed hybrid methods and a metaheuristic that outperformed the pure MIP formulations, being practical to deal with the PLSVSP. A simheuristic using embedded Monte Carlo simulation was developed for the stochastic variant of the problem, considering uncertainties in the connection duration and the arrival dates of pipelines at the port. The results show a significant improvement in the solutions dealing with uncertainties compared to solutions generated by a deterministic method. The use of simulation within a metaheuristic framework proved to be a promising approach, being able to deal with the stochastic problem, with little extra computational effort required.