Relações min-max são objetos centrais em otimização combinatória. Elas basicamente afirmam que, numa dada estrutura, o valor ótimo de um certo problema de minimização é igual ao valor ótimo de um outro problema de maximização. Relações desse tipo fornecem boas caracterizações e descrições poliédricas para diversos problemas importantes, além de geralmente virem acompanhadas de algoritmos eficientes para os problemas em questão. Muitas vezes, tais algoritmos eficientes são obtidos naturalmente das provas construtivas dessas relações; mesmo quando isso não ocorre, essas relações revelam o suficiente sobre a estrutura combinatória dos problemas, levando ao desenvolvimento de algoritmos eficientes. O foco principal desta dissertação é o estudo dessas relações em grafos. Nossa ênfase é sobre grafos orientados. Apresentamos o poderoso arcabouço poliédrico de Edmonds e Giles envolvendo fluxos submodulares, bem como o algoritmo de Frank para um caso especial desse arcabouço: o teorema de Lucchesi-Younger. Derivamos também diversas relações min-max sobre o empacotamento de conectores, desde o teorema de ramificações disjuntas de Edmonds até o teorema de junções disjuntas de Feofiloff-Younger e Schrijver. Apresentamos também uma resenha completa sobre as conjecturas de Woodall e sua versão capacitada, conhecida como conjectura de Edmonds-Giles. Derivamos ainda algumas relações min-max clássicas sobre emparelhamentos, T-junções e S-caminhos. Para tanto, usamos um teorema de Frank, Tardos e Sebö e um arcabouço bastante geral devido a Chudnovsky, Geelen, Gerards, Goddyn, Lohman e Seymour. Ao longo do texto, ilustramos vários aspectos recorrentes, como o uso de ferramentas da combinatória poliédrica, a técnica do descruzamento, o uso de funções submodulares, matróides e propriedades de troca, bem como alguns resultados envolvendo subestruturas proibidas. / Min-max relations are central objects in combinatorial optimization. They basically state that, in a given structure, the optimum value of a certain minimization problem equals the optimum value of a different, maximization problem. Relations of this kind provide good characterizations and polyhedral descriptions to several important problems and, moreover, they often come with efficient algorithms for the corresponding problems. Usually, such efficient algorithms are obtained naturally from the constructive proofs involved; even when that is not the case, these relations reveal enough of the combinatorial structure of the problem, leading to the development of efficient algorithms. The main focus of this dissertation is the study of these relations in graphs. Our emphasis is on directed graphs. We present Edmonds and Giles\' powerful polyhedral framework concerning submodular flows, as well as Frank\'s algorithm for a special case of this framework: the Lucchesi-Younger Theorem. We also derive several min-max relations about packing connectors, starting with Edmonds\' Disjoint Branchings Theorem and ending with Feofiloff-Younger and Schrijver\'s Disjoint Dijoins Theorem. We further derive some classical min-max relations on matchings, T-joins and S-paths. To this end, we use a theorem due to Frank, Tardos, and Sebö and a general framework due to Chudnovsky, Geelen, Gerards, Goddyn, Lohman, and Seymour. Throughout the text, we illustrate several recurrent themes, such as the use of tools from polyhedral combinatorics, the uncrossing technique, the use of submodular functions, matroids and exchange properties, as well as some results involving forbidden substructures.

Relações min-max são objetos centrais em otimização combinatória. Elas basicamente afirmam que, numa dada estrutura, o valor ótimo de um certo problema de minimização é igual ao valor ótimo de um outro problema de maximização. Relações desse tipo fornecem boas caracterizações e descrições poliédricas para diversos problemas importantes, além de geralmente virem acompanhadas de algoritmos eficientes para os problemas em questão. Muitas vezes, tais algoritmos eficientes são obtidos naturalmente das provas construtivas dessas relações; mesmo quando isso não ocorre, essas relações revelam o suficiente sobre a estrutura combinatória dos problemas, levando ao desenvolvimento de algoritmos eficientes. O foco principal desta dissertação é o estudo dessas relações em grafos. Nossa ênfase é sobre grafos orientados. Apresentamos o poderoso arcabouço poliédrico de Edmonds e Giles envolvendo fluxos submodulares, bem como o algoritmo de Frank para um caso especial desse arcabouço: o teorema de Lucchesi-Younger. Derivamos também diversas relações min-max sobre o empacotamento de conectores, desde o teorema de ramificações disjuntas de Edmonds até o teorema de junções disjuntas de Feofiloff-Younger e Schrijver. Apresentamos também uma resenha completa sobre as conjecturas de Woodall e sua versão capacitada, conhecida como conjectura de Edmonds-Giles. Derivamos ainda algumas relações min-max clássicas sobre emparelhamentos, T-junções e S-caminhos. Para tanto, usamos um teorema de Frank, Tardos e Sebö e um arcabouço bastante geral devido a Chudnovsky, Geelen, Gerards, Goddyn, Lohman e Seymour. Ao longo do texto, ilustramos vários aspectos recorrentes, como o uso de ferramentas da combinatória poliédrica, a técnica do descruzamento, o uso de funções submodulares, matróides e propriedades de troca, bem como alguns resultados envolvendo subestruturas proibidas. / Min-max relations are central objects in combinatorial optimization. They basically state that, in a given structure, the optimum value of a certain minimization problem equals the optimum value of a different, maximization problem. Relations of this kind provide good characterizations and polyhedral descriptions to several important problems and, moreover, they often come with efficient algorithms for the corresponding problems. Usually, such efficient algorithms are obtained naturally from the constructive proofs involved; even when that is not the case, these relations reveal enough of the combinatorial structure of the problem, leading to the development of efficient algorithms. The main focus of this dissertation is the study of these relations in graphs. Our emphasis is on directed graphs. We present Edmonds and Giles\' powerful polyhedral framework concerning submodular flows, as well as Frank\'s algorithm for a special case of this framework: the Lucchesi-Younger Theorem. We also derive several min-max relations about packing connectors, starting with Edmonds\' Disjoint Branchings Theorem and ending with Feofiloff-Younger and Schrijver\'s Disjoint Dijoins Theorem. We further derive some classical min-max relations on matchings, T-joins and S-paths. To this end, we use a theorem due to Frank, Tardos, and Sebö and a general framework due to Chudnovsky, Geelen, Gerards, Goddyn, Lohman, and Seymour. Throughout the text, we illustrate several recurrent themes, such as the use of tools from polyhedral combinatorics, the uncrossing technique, the use of submodular functions, matroids and exchange properties, as well as some results involving forbidden substructures.

In this dissertation, we study several problems related to intervals and develop efficient algorithms for them. Interval problems have many applications in reality because many objects, values, and ranges are intervals in nature, such as time intervals, distances, line segments, probabilities, etc. Problems on intervals are gaining attention also because intervals are among the most basic geometric objects, and for the same reason, computational geometry techniques find useful for attacking these problems. Specifically, the problems we study in this dissertation includes the following: balanced splitting on weighted intervals, minimizing the movements of spreading points, dispersing points on intervals, multiple barrier coverage, and separating overlapped intervals on a line. We develop efficient algorithms for these problems and our results are either first known solutions or improve the previous work. In the problem of balanced splitting on weighted intervals, we are given a set of n intervals with non-negative weights on a line and an integer k ≥ 1. The goal is to find k points to partition the line into k + 1 segments, such that the maximum sum of the interval weights in these segments is minimized. We give an algorithm that solves the problem in O(n log n) time. Our second problem is on minimizing the movements of spreading points. In this problem, we are given a set of points on a line and we want to spread the points on the line so that the minimum pairwise distance of all points is no smaller than a given value δ. The objective is to minimize the maximum moving distance of all points. We solve the problem in O(n) time. We also solve the cycle version of the problem in linear time. For the third problem, we are given a set of n non-overlapping intervals on a line and we want to place a point on each interval so that the minimum pairwise distance of all points are maximized. We present an O(n) time algorithm for the problem. We also solve its cycle version in O(n) time. The fourth problem is on multiple barrier coverage, where we are given n sensors in the plane and m barriers (represented by intervals) on a line. The goal is to move the sensors onto the line to cover all the barriers such that the maximum moving distance of all sensors is minimized. Our algorithm for the problem runs in O(n2 log n log log n + nm log m) time. In a special case where the sensors are all initially on the line, our algorithm runs in O((n + m) log(n + m)) time. Finally, for the problem of separating overlapped intervals, we have a set of n intervals (possibly overlapped) on a line and we want to move them along the line so that no two intervals properly intersect. The objective is to minimize the maximum moving distance of all intervals. We propose an O(n log n) time algorithm for the problem. The algorithms and techniques developed in this dissertation are quite basic and fundamental, so they might be useful for solving other related problems on intervals as well.

[pt] A receita arrecadada pelo uso do sistema de transmissão é utilizada para cobrir custos de planejamento, operação e manutenção e deve ser paga por geradores e demandas, que são usuários do sistema. Um dos principais desafios é determinar a melhor maneira de alocar estes custos a geradores e demandas. Em países em desenvolvimento, como o Brasil, a acelerada expansão de geração e de transmissão, desencadeada por um crescimento acentuado de demanda, pode provocar significativa volatilidade e dispersão entre as tarifas dos usuários do sistema. Estes efeitos criam um ambiente inseguro para os investidores em geração. Para tratar este problema, esta dissertação propõe um novo método de alocação de custos pelo uso da transmissão que utiliza uma abordagem baseada na técnica de otimização min-max, e no método Nodal utilizado no Brasil. O propósito contido na utilização da técnica min-max é que os usuários com as piores tarifas devem ter prioridade em minimizá-las no processo de otimização. Assim, o objetivo é fornecer uma solução mais equitativa, e conseqüentemente, a redução de dispersão e volatilidade das tarifas ao longo do tempo, quando novos investimentos em geração e transmissão são feitos no sistema. Os resultados obtidos nos sistemas IEEE 24 barras e IEEE 118 barras indicam que a abordagem proposta fornece tarifas menos dispersas comparadas com outros métodos existentes, mas mantendo características desejáveis do método Nodal original. O método proposto também apresenta menos volatilidade nas tarifas no caso de mudanças (como diferentes despachos de geração) no sistema. / [en] The revenue accrued for the use of the transmission system is used to recover the cost of planning, operation and maintenance and must be paid by generators and loads, which are the users of the system. One of the main challenges is how to establish the best way to allocate these costs to generators and loads. In developing countries, like Brazil, fast generation and transmission expansion triggered by a sharp demand growth, can cause significant volatility and dispersion among agents transmission tariffs. These effects can create an unsafe environment for new investors in generation. In order to face this problem, this dissertation proposes a new transmission cost allocation method that utilizes an approach based on the min-max optimization technique, and on the nodal method used in Brazil. The idea behind the utilization of min-max method is that the agents with the worst tariffs should have priority in the tariff optimization process. Thus, the objective is to provide an equitable solution and, consequently, a reduction of the dispersion and volatility of the tariffs over time, when new transmission or generation assets are incorporated into the system. The results presented for IEEE 24 bus and IEEE 118 bus systems indicate that the proposed approach gives less-dispersed tariffs compared with other existing methods, but keeping the desirable features of the traditional nodal method. The proposed method also shows less volatility in tariffs if changes (like different generation dispatches) are made to the system.

The diploma thesis is focused on inventory management in a production company with an emphasis on optimizing company´s stock level. There has been made an analysis of the current status of selected group of inventory, and of the use of the existing information system. Based on this analysis and theoretical knowledge of inventory management, two measures have been designed. They should help to increase efficiency of purchasing and to reduce inventory and costs.

<p>In this thesis we are concerned with the complexity of formalizing reasoning in Combinatorial Matrix Theory (CMT). We are interested in the strength of the bounded arithmetic theories necessary in order to prove the fundamental results of this field. Bounded Arithmetic can be seen as the uniform counterpart of Propositional Proof Complexity.</p> <p>Perhaps the most famous and fundamental theorem in CMT is the K{\"o}nig's Min-Max Theorem $(\KMM)$ which arises naturally in all areas of combinatorial algorithms. As far as we know, in this thesis we give the first feasible proof of $\KMM$. Our results show that Min-Max reasoning can be formalized with uniform Extended Frege.</p> <p>We show, by introducing new proof techniques, that the first order theory $\LA$ with induction restricted to $\Sigma_1^B$ formulas---i.e., restricted to bounded existential matrix quantification---is sufficient to formalize a large portion of CMT, in particular $\KMM$. $\Sigma_1^B$-$\LA$ corresponds to polynomial time reasoning, also known as $\ELA$.</p> <p>While we consider matrices over $\{0,1\}$, the underlying ring is $\mathbb{Z}$, since we require that $\Sigma A$ compute the number of 1s in the matrix $A$ (which for a 0-1 matrix is simply the sum of all entries---meaning $\Sigma A$). Thus, over $\mathbb{Z}$, $\LA$ translates to $\TC^0$-Frege, while, as mentioned before, $\ELA$ translates into Extended Frege.</p> <p>In order to prove $\KMM$ in $\ELA$, we need to restrict induction to $\Sigma_1^B$ formulas. The main technical contribution is presented in Claim~4.3.4, ~Section~4.3.3. Basically, we introduce a polynomial time procedure, whose proof of correctness can be shown with $\ELA$, that works as follow: given a matrix of size $e \times f$ such that $e\leq f$, where the minimum cover is of size $e$, our procedure computes a maximum selection of size $e$, row by row.</p> <p>Furthermore, we show that Menger's Theorem, Hall's Theorem, and Dilworth's Theorem---theorems related to $\KMM$---can also be proven feasibly; in fact, all these theorems are equivalent to KMM, and the equivalence can be shown in $\LA$. We believe that this captures the proof complexity of Min-Max reasoning rather completely.</p> <p>We also present a new Permutation-Based algorithm for computing a Minimum Vertex Cover from a Maximum Matching in a bipartite graph. Our algorithm is linear-time and computationally very simple: it permutes the rows and columns of the matrix representation of the bipartite graph in order to extract the vertex cover from a maximum matching in a recursive fashion. Our Permutation-Based algorithm uses properties of $\KMM$ Theorem and it is interesting for providing a new permutation---and CMT---perspective on a well-known problem.</p> / Doctor of Philosophy (PhD)

Esta dissertação de mestrado aborda o problema de regulação robusta recursiva para sistemas lineares discretos sujeitos a incertezas paramétricas. Um novo funcional quadrático, baseado na combinação de função penalidade e função custo do tipo jogos, é projetado para lidar com este problema. Uma característica interessante desta abordagem é que a recursividade pode ser realizada sem a necessidade do ajuste de parâmetros auxiliares. Bastante útil para aplicações online. A solução proposta é baseada numa equação recursiva de Riccati. Também, a convergência e a estabilidade do regulador para o sistema linear incerto invariante no tempo são garantidas. / This dissertation deals with robust recursive regulators for discrete-time systems subject to parametric uncertainties. A new quadratic functional based on the combination of penalty functions and game theory is proposed to solve this class of problems. An important issue of this approach is that the recursiveness can be performed without the need of adjusting auxiliary parameters. It is useful for online applications. The solution proposed is based on Riccati equation which guarantees the convergence and stability of the time-invariant system.

Esta dissertação de mestrado aborda o problema de regulação robusta recursiva para sistemas lineares discretos sujeitos a incertezas paramétricas. Um novo funcional quadrático, baseado na combinação de função penalidade e função custo do tipo jogos, é projetado para lidar com este problema. Uma característica interessante desta abordagem é que a recursividade pode ser realizada sem a necessidade do ajuste de parâmetros auxiliares. Bastante útil para aplicações online. A solução proposta é baseada numa equação recursiva de Riccati. Também, a convergência e a estabilidade do regulador para o sistema linear incerto invariante no tempo são garantidas. / This dissertation deals with robust recursive regulators for discrete-time systems subject to parametric uncertainties. A new quadratic functional based on the combination of penalty functions and game theory is proposed to solve this class of problems. An important issue of this approach is that the recursiveness can be performed without the need of adjusting auxiliary parameters. It is useful for online applications. The solution proposed is based on Riccati equation which guarantees the convergence and stability of the time-invariant system.

No description available.

Edmonds and Giles conjectured that the maximum number of directed joins in a packing is equal to the minimum weight of a directed cut, for any weighted directed graph. This is a generalization of Woodall's Conjecture (which is still open). Schrijver found the first known counterexample to the Edmonds-Giles Conjecture, while Cornuejols and Guenin found the next two. In this thesis we introduce new counterexamples, and prove that all minimal counterexamples of a certain type have now been found.