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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
51

O remodelado papel das áreas de compras: o manejo da demanda e a programação matemática como indutores de eficiência na aquisição. / The redesigned role of purchasing departments: demand management and mathematical programming lead to efficiency in acquisitions.

Vizzoto, Felipe 25 November 2016 (has links)
Um mercado globalizado altamente competitivo e a crescente horizontalização das cadeias de abastecimento realçam a importância da racionalização dos custos e da adequada seleção de fornecedores. Esses mesmos fatores, no entanto, agravam a complexidade envolvida no desempenhar dessas tarefas. A fim de desatar tais nós, o presente trabalho propõe uma abordagem para a seleção de fornecedores que conjuga técnicas de programação matemática que permitam a exploração de economias de escala e escopo a uma metodologia inovadora para construção de cenários de demanda baseada em conceitos modernos de suprimentos. O resultado desta abordagem foi um modelo de programação inteira mista visando a minimização dos custos por desempenho adquirido. Os resultados obtidos na aplicação a um caso hipotético relevam efetividade na redução dos custos, sem prejuízo à qualidade dos materiais adquiridos. O impacto nos custos decorre da reconfiguração da demanda, aumento do poder de barganha interno e externo e aproveitamento de ganhos de escala e escopo. / A highly competitive globalized market and a growingly horizontalization through supply chains highlight the importance of properly selecting suppliers and managing costs. These same factors, however, increase the complexity in performing such tasks. In order to solve this plot, it is presented in this work an approach for supplier selection connecting mathematical programming techniques, which allow the use of economies of scope and scale, and an innovative methodology that applies modern concepts of purchasing management for constructing new demand scenarios. From this approach a mixed integer programming model derives, with the goal of minimizing costs per performance acquired. The results of its application in a hypothetical case reveal the effectiveness of the approach in reducing the costs with no significant impact on the acquired performance. This is explained by the reconfiguration of the demand, a shift in the bargaining power within and out of the company and the incorporation of economies of scope and scale.
52

Mathematical models and heuristic methods for nesting problems / Modelos matemáticos e métodos heurísticos para os problemas de corte de itens irregulares

Mundim, Leandro Resende 18 August 2017 (has links)
Irregular cutting and packing problems, with convex and non-convex polygons, are found in many industries such as metal mechanics, textiles, of shoe making, the furniture making and others. In this thesis we study the two-dimensional version of these problems, where we want to allocate a set of items, without overlap, inside one or more containers, limited or unlimited, so as to optimize an objective function. In this document we study the knapsack problem, placement problem, strip packing problem, cutting stock problem and bin packing problem. For these problems, the heuristic methods and mathematical programming models are proposed and presented very promising results, surpassing in many cases the best results in the specialized literature. This thesis is organized as follows. In Chapter 1, we present a review of the studied problems, the value proposition for this thesis with the main contributions and ideas. In Chapter 2, we propose a metaheursitic for the strip packing problem with irregular items and circles. Then, in Chapter 3, we present a generic heuristic for the allocation of irregular items that may be weakly or strongly heterogeneous and will be allocated in a container (output maximization problems) or multiple containers (input minimization problems). In Chapter 4, we propose a solution method for the cutting stock problem with deterministic demand and stochastic demand. In Chapters 5 and 6, we present mathematical programming models for the strip packing problem. Finally, in Chapter 7, we present a conclusion and a concise direction for future works. / Os problemas de corte e empacotamento de itens irregulares, polígonos convexos e não convexos, são encontrado em diversas indústrias, tais como a metal-mecânica, a têxtil, a de calçados, a moveleira e outras. Nesta tese estudamos a versão bidimensional destes problemas, na qual desejamos alocar um conjunto de itens, sem sobreposição, no interior de um ou mais recipientes, limitados ou ilimitados, de modo a otimizar uma função objetivo. Neste trabalho estudamos o problema da mochila, o problema do assentamento, o problema empacotamento em faixa, o problema de corte de estoque e o problema de empacotamento de contêineres. Para estes problemas, os métodos heurísticos e modelos de programação matemática propostos e apresentam resultados muito promissores, ultrapassando em muitos casos os melhores resultados da literatura especializada. Esta tese esta organizada da seguinte maneira. No Capítulo 1, apresentamos uma revisão dos problemas estudados, a proposta de valor deste doutorado com as principais contribuições e ideias. No Capítulo 2, propomos uma meta-heurística para o problema de empacotamento em faixa para itens irregulares e círculos. Em seguida, no Capítulo 3 apresentamos uma heurística genérica para a alocação de itens irregulares que podem ser fracamente ou fortemente heterogêneos e serão alocados em um recipiente (problema de maximização de saída) ou de múltiplos recipientes (problemas de minimização de entrada). O Capítulo 4 propõem um método de solução para o problema de corte de estoque com demanda conhecida e demanda estocástica. Nos Capítulos 5 e 6 apresentamos modelos de programação matemática para o problema de corte de itens irregulares em faixa. Finalmente, no Capítulo 7, apresentamos a conclusão e uma sucinta direção para os trabalhos futuros.
53

Otimização das movimentações de lotes de derivados de petróleo e de biocombustíveis pela rede logística brasileira de petróleo: conceitos, modelagem e aplicação

Aizemberg, Luiz 27 July 2017 (has links)
Submitted by Secretaria Pós de Produção (tpp@vm.uff.br) on 2017-07-27T19:52:32Z No. of bitstreams: 1 D2014 - Luiz Aizemberg.pdf: 13176203 bytes, checksum: 7bf48143ab75b243fe03ef2cad6ef82b (MD5) / Made available in DSpace on 2017-07-27T19:52:32Z (GMT). No. of bitstreams: 1 D2014 - Luiz Aizemberg.pdf: 13176203 bytes, checksum: 7bf48143ab75b243fe03ef2cad6ef82b (MD5) / Nesta tese de doutorado, foram estudados modelos matemáticos e outras técnicas de otimização para um problema de nível tático de transporte de óleo e derivados. O problema monoproduto e monomodal considera capacidades de estoque e tamanhos de lote discretos a serem transportados, objetivando atender as demandas ao longo de um horizonte de tempo. Testes exaustivos foram realizados com 75 instâncias retiradas da literatura e com 25 novas instâncias com maior grau de dificuldade do que as já existentes. Uma heurística baseada em geração de colunas foi desenvolvida para encontrar boas soluções viáveis em menos tempo do que os algoritmos heurísticos do otimizador comercial utilizado. Este estudo foi posteriormente utilizado no desenvolvimento de um modelo matemático multiproduto e multimodal, onde diversas restrições encontradas no planejamento logístico de uma empresa de petróleo são consideradas. Nesta etapa, foram pesquisadas e testadas técnicas de otimização com maior aderência a modelos matemáticos complexos. Optou-se por mudar o foco de métodos exatos para heurísticos. Uma heurística baseada em busca local foi construída e sua eficiência comprovada. Além das instâncias utilizadas no estudo anterior, instâncias baseadas em dados reais foram utilizadas, o que permitiu testar todas as restrições do modelo. / In this thesis, we study tactical models and other optimization techniques for a crude oil transportation problem. The problem with one product and one transportation mode considers inventory capacities and discrete lot sizes to be transported, aiming at meeting given demands over a finite time horizon. We use 75 instances from the literature and propose 25 new harder ones. A column generation-based heuristic is proposed to find good feasible solutions with less computational burden than the heuristics of the commercial solver used. The optimization study is then used in the development of a mathematical model with several products and transportation modes, where many real constraints found in the logistic management of a petroleum company are considered. Optimization techniques more adherent to complex mathematical models are studied. The focus changed from exact to heuristic methods. A local search heuristic was devised and its efficiency comproved. Instances from the previous study and new instances based on real data are used. These new instances allow testing the new constraints added in the model.
54

ROI: An extensible R Optimization Infrastructure

Theußl, Stefan, Schwendinger, Florian, Hornik, Kurt 01 1900 (has links) (PDF)
Optimization plays an important role in many methods routinely used in statistics, machine learning and data science. Often, implementations of these methods rely on highly specialized optimization algorithms, designed to be only applicable within a specific application. However, in many instances recent advances, in particular in the field of convex optimization, make it possible to conveniently and straightforwardly use modern solvers instead with the advantage of enabling broader usage scenarios and thus promoting reusability. This paper introduces the R Optimization Infrastructure which provides an extensible infrastructure to model linear, quadratic, conic and general nonlinear optimization problems in a consistent way. Furthermore, the infrastructure administers many different solvers, reformulations, problem collections and functions to read and write optimization problems in various formats. / Series: Research Report Series / Department of Statistics and Mathematics
55

Evaluating Flexibility Metrics on Simple Temporal Networks with Reinforcement Learning

Khan, Hamzah I 01 January 2018 (has links)
Simple Temporal Networks (STNs) were introduced by Tsamardinos (2002) as a means of describing graphically the temporal constraints for scheduling problems. Since then, many variations on the concept have been used to develop and analyze algorithms for multi-agent robotic scheduling problems. Many of these algorithms for STNs utilize a flexibility metric, which measures the slack remaining in an STN under execution. Various metrics have been proposed by Hunsberger (2002); Wilson et al. (2014); Lloyd et al. (2018). This thesis explores how adequately these metrics convey the desired information by using them to build a reward function in a reinforcement learning problem.
56

Mathematical programming techniques for solving stochastic optimization problems with certainty equivalent measures of risk

Vinel, Alexander 01 May 2015 (has links)
The problem of risk-averse decision making under uncertainties is studied from both modeling and computational perspectives. First, we consider a framework for constructing coherent and convex measures of risk which is inspired by infimal convolution operator, and prove that the proposed approach constitutes a new general representation of these classes. We then discuss how this scheme may be effectively employed to obtain a class of certainty equivalent measures of risk that can directly incorporate decision maker's preferences as expressed by utility functions. This approach is consequently utilized to introduce a new family of measures, the log-exponential convex measures of risk. Conducted numerical experiments show that this family can be a useful tool when modeling risk-averse decision preferences under heavy-tailed distributions of uncertainties. Next, numerical methods for solving the rising optimization problems are developed. A special attention is devoted to the class p-order cone programming problems and mixed-integer models. Solution approaches proposed include approximation schemes for $p$-order cone and more general nonlinear programming problems, lifted conic and nonlinear valid inequalities, mixed-integer rounding conic cuts and new linear disjunctive cuts.
57

Fast Polyhedral Adaptive Conjoint Estimation

Olivier, Toubia, Duncan, Simester, John, Hauser 02 1900 (has links)
We propose and test a new adaptive conjoint analysis method that draws on recent polyhedral “interior-point” developments in mathematical programming. The method is designed to offer accurate estimates after relatively few questions in problems involving many parameters. Each respondent’s ques-tions are adapted based upon prior answers by that respondent. The method requires computer support but can operate in both Internet and off-line environments with no noticeable delay between questions. We use Monte Carlo simulations to compare the performance of the method against a broad array of relevant benchmarks. While no method dominates in all situations, polyhedral algorithms appear to hold significant potential when (a) metric profile comparisons are more accurate than the self-explicated importance measures used in benchmark methods, (b) when respondent wear out is a concern, and (c) when product development and/or marketing teams wish to screen many features quickly. We also test hybrid methods that combine polyhedral algorithms with existing conjoint analysis methods. We close with suggestions on how polyhedral methods can be used to address other marketing problems. / Sloan School of Management and the Center for Innovation in Product Development at MIT
58

Intégration d'exigences de haut niveau dans les problèmes d'optimisation : théorie et applications

Roda, Fabio 01 March 2013 (has links) (PDF)
Nous utilisons, ensemble, l'Ingénierie Système et la Programmation mathématique pour intégrer les exigences de haut niveau dans des problèmes d'optimisation. Nous appliquons cette méthode à trois types différents de système. (1) Les Systèmes d'Information (SI), c.à.d. les réseaux des ressources, matérielles, logicielles et utilisateurs, utilisés dans une entreprise, doivent fournir la base des projets qui sont lancés pour répondre aux besoins commerciaux/des affaires (business). Les SI doivent être capables d'évoluer au fil des remplacements d'une technologie par une autre. Nous proposons un modèle opérationnel et une formulation de programmation mathématique qui formalise un problème de priorisation qui se présente dans le contexte de l'évolution technologique d'un système d'information. (2) Les Recommender Systems (RS) sont un type de moteur de recherche dont l'objectif est de fournir des recommandations personnalisées. Nous considérons le problème du design des Recommender Systems dans le but de fournir de bonnes, intéressantes et précises suggestions. Le transport des matériaux dangereux entraine plusieurs problèmes liés aux conséquences écologiques des incidents possibles. (3) Le système de transport doit assurer le transport, pour l'élimination en sécurité des déchets dangereux, d'une façon telle que le risque des possibles incidents soit distribué d'une manière équitable parmi la population. Nous considérons et intégrons dans des formulations de programmation mathématique deux idées différentes d'équité.
59

Modelling environment for the design and optimisation of energy polygeneration systems

Ortiga Guillén, Jordi 01 July 2010 (has links)
The optimal design and operation of an energy supply system is very important for the matching of the energy production and consumption especially in the residential-tertiary sector characterized by an energy demand with a high variability. The main objective of this thesis is to develop an optimisation environment for the preliminary design and analysis of polygeneration plants. The optimisation models are organized in different units represented by blocks that can be connected between each other to create the flowsheet of the polygeneration system. To characterize the energy demand in the residential and tertiary sector a graphic methodology has been developed to select typical energy demand days from a yearly energy demand profile. The environment developed has been applied to two case studies: a small scale polygeneration plant using a liquid desiccant system for air conditioning and a polygeneration plant connected to a district heating and cooling network.
60

New Benders' Decomposition Approaches for W-CDMA Telecommunication Network Design

Naoum-Sawaya, Joe January 2007 (has links)
Network planning is an essential phase in successfully operating state-of-the-art telecommunication systems. It helps carriers increase revenues by deploying the right technologies in a cost effective manner. More importantly, through the network planning phase, carriers determine the capital needed to build the network as well as the competitive pricing for the offered services. Through this phase, radio tower locations are selected from a pool of candidate locations so as to maximize the net revenue acquired from servicing a number of subscribers. In the Universal Mobile Telecommunication System (UMTS) which is based on the Wideband Code Division Multiple Access scheme (W-CDMA), the coverage area of each tower, called a cell, is not only affected by the signal's attenuation but is also affected by the assignment of the users to the towers. As the number of users in the system increases, interference levels increase and cell sizes decrease. This complicates the network planning problem since the capacity and coverage problems cannot be solved separately. To identify the optimal base station locations, traffic intensity and potential locations are determined in advance, then locations of base stations are chosen so as to satisfy minimum geographical coverage and minimum quality of service levels imposed by licensing agencies. This is implemented through two types of power control mechanisms. The power based power control mechanism, which is often discussed in literature, controls the power of the transmitted signal so that the power at the receiver exceeds a given threshold. On the other hand, the signal-to-interference ratio (SIR) based power control mechanism controls the power of the transmitted signal so that the ratio of the power of the received signal over the power of the interfering signals exceeds a given threshold. Solving the SIR based UMTS/W-CDMA network planning problem helps network providers in designing efficient and cost effective network infrastructure. In contrast to the power based UMTS/W-CDMA network planning problem, the solution of the SIR based model results in higher profits. In SIR based models, the power of the transmitted signals is decreased which lowers the interference and therefore increases the capacity of the overall network. Even though the SIR based power control mechanism is more efficient than the power based power control mechanism, it has a more complex implementation which has gained less attention in the network planning literature. In this thesis, a non-linear mixed integer problem that models the SIR based power control system is presented. The non-linear constraints are reformulated using linear expressions and the problem is exactly solved using a Benders decomposition approach. To overcome the computational difficulties faced by Benders decomposition, two novel extensions are presented. The first extension uses the analytic center cutting plane method for the Benders master problem, in an attempt to reduce the number of times the integer Benders master problem is solved. Additionally, we describe a heuristic that uses the analytic center properties to find feasible solutions for mixed integer problems. The second extension introduces a combinatorial Benders decomposition algorithm. This algorithm may be used for solving mixed integer problems with binary variables. In contrast to the classical Benders decomposition algorithm where the master problem is a mixed integer problem and the subproblem is a linear problem, this algorithm decomposes the problem into a mixed integer master problem and a mixed integer subproblem. The subproblem is then decomposed using classical Benders decomposition, leading to a nested Benders algorithm. Valid cuts are generated at the classical Benders subproblem and are added to the combinatorial Benders master problem to enhance the performance of the algorithm. It was found that valid cuts generated using the analytic center cutting plane method reduce the number of times the integer Benders master problem is solved and therefore reduce the computational time. It was also found that the combinatorial Benders reduces the complexity of the integer master problem by reducing the number of integer variables in it. The valid cuts generated within the nested Benders algorithm proved to be beneficial in reducing the number of times the combinatorial Benders master problem is solved and in reducing the computational time that the overall algorithm takes. Over 110 instances of the UMTS/W-CDMA network planning problem ranging from 20 demand points and 10 base stations to 140 demand points and 30 base stations are solved to optimality.

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