Submitted by WALDEMAR PEREIRA MATHIAS NETO null (waldemarmathias@gmail.com) on 2016-10-04T02:26:06Z No. of bitstreams: 1 MATHIAS-NETO-TESE-2016.pdf: 2428868 bytes, checksum: 0bbed2a47b06389d32f691db8e5364cd (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-10-07T13:22:18Z (GMT) No. of bitstreams: 1 mathiasneto_wp_dr_ilha.pdf: 2428868 bytes, checksum: 0bbed2a47b06389d32f691db8e5364cd (MD5) / Made available in DSpace on 2016-10-07T13:22:18Z (GMT). No. of bitstreams: 1 mathiasneto_wp_dr_ilha.pdf: 2428868 bytes, checksum: 0bbed2a47b06389d32f691db8e5364cd (MD5) Previous issue date: 2016-08-05 / Fundação de Ensino, Pesquisa e Extensão de Ilha Solteira (FEPISA) / Os modernos sistemas aéreos de distribuição de energia elétrica são projetados para operar com altos índices de confiabilidade. Todavia, interrupções de fornecimento podem ocorrer a qualquer momento e causadas pelos mais diversos fatores, tais como, vendavais, árvores, ou ainda, colisão de veículos com a rede. Portanto, para garantir o mínimo impacto destas interrupções nos índices de confiabilidade da rede, áreas sem fornecimento devem ser reenergizadas tão rá- pido quanto possível. Este processo de reenergização do sistema é comumente denominado restauração. O principal objetivo do processo de restauração é restabelecer o maior número de cargas, no menor intervalo de tempo possível, por meio de uma sequência de aberturas e fechamentos de chaves de manobras. A existência de um conjunto de chaves seccionadoras estrategicamente posicionadas na rede permite que a estrutura malhada dos sistemas de distribuição opere com topologias radiais. Portanto, a execução de uma sequência de manobras é capaz de alterar a topologia radial da rede e restabelecer as cargas previamente sem fornecimento de energia. Este trabalho propõe uma nova metodologia para solução do problema de restauração de sistemas de distribuição de energia elétrica baseado no uso conjunto da meta-heurística de busca tabu, a representação nó-profundidade (RNP) e seus operadores PAO e CAO. Os operadores da RNP são empregados para originar a vizinhança da meta-heurística de busca tabu. Um novo operador foi introduzido e alterações nos demais operadores foram realizadas para possibilitar soluções factíveis em sistemas com alto carregamento. O problema é formulado através de um modelo não linear inteiro misto e considera a minimização dos custo da interrupção não programada como objetivo do problema. Os limites operacionais da rede são avaliados durante o intervalo previsto para a rede permanecer no estado restaurativo. Estes limites caracterizam as restrições do problema. Ao modelo matemático foi incluído a geração distribuída e cargas remotamente controladas como ferramentas de apoio à restauração. Os geradores distribuídos são modelados através de curvas horárias de geração, em função de sua tecnologia, e as cargas são modeladas através de curvas que consideram o perfil de consumo. Adicionalmente, cargas controladas termostaticamente também foram incluídas ao modelo. Por fim, a técnica de solução proposta é avaliada através de um sistema teste baseado no sistema de distribuição IEEE de 37 barras em oito diferentes cenários. Os resultados obtidos indicam a viabilidade da metodologia para a solução do problema de restauração de sistemas de distribui- ção. / The modern overhead power distribution systems are designed to operate with high reliability indices. However, power outages may occur at any time and caused by several factors, such aswindstorms, trees or vehicle collision with the network. Therefore, to ensure minimal impact of these interruptions in network reliability indices, out-of-service areas, which are not affected by the permanent fault, should be re-energized as fast as possible. The process of system reenergizing is called restoration. The main purpose of restoration process is to restore the largest amount of load, as fast as possible, through a sequence of switching actions. The existence of several switchgears, strategically allocated in the network, allows the meshed distribution systems work with radial topologies. Therefore, performing a sequence of maneuvers, automatically or manually, may change the radial grid topology and restore the loads previously without a power supply. This work proposes a new methodology to solve the distribution system restoration problem based on the joint use of tabu search meta-heuristic, the node-depth encoding (NDE) and its operators (PAO and CAO). The NDE operators are used to buid the neighborhood of tabu search meta-heuristic. A new operator was introduced and changes in other operators were carried out to allow feasible solutions in systems with heavy loading. The proposed mathematical model minimize the cost of unscheduled outage aim of the problem. The problem of restrictions are characterized by the operating limits of the network and evaluated periodically while the network remains in the restorative state. Additionally, the use of distributed generation and controlled remotely loads are considered to support the restoration tools. The problem is formulated as a nonlinear mixed-integer model. The main goal is minimize the cost of unscheduled interruption. The operating limits of the network are evaluated while it remains in the restorative state.. These limits characterize the constraints of the problem. At the mathematical model was included distributed generation and loads remotely controlled as support tools. The distributed generators are modeled by its hourly curves and the loads are modeled through curves with their consumption profile. Additionally, controlled thermostatically loads were also included into the mathematical model. Finally, the proposed solution is evaluated through a modified test system based on the IEEE 37-bus feeder test system. Eight different scenarios was evaluated. The results indicate the feasibility of the methodology to solve the distribution systems restoration problem. / FEPISA: 011/2011

Submitted by MARCEL CHUMA CERBANTES null (marcel.chuma@gmail.com) on 2017-04-16T19:19:19Z No. of bitstreams: 1 phd_dissertation_marcel_chuma_cerbantes.pdf: 2683152 bytes, checksum: bb2fddaeed33cb6c6ee2f902e3624178 (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-04-18T17:43:20Z (GMT) No. of bitstreams: 1 chumacerbantes_m_dr_ilha.pdf: 2683152 bytes, checksum: bb2fddaeed33cb6c6ee2f902e3624178 (MD5) / Made available in DSpace on 2017-04-18T17:43:20Z (GMT). No. of bitstreams: 1 chumacerbantes_m_dr_ilha.pdf: 2683152 bytes, checksum: bb2fddaeed33cb6c6ee2f902e3624178 (MD5) Previous issue date: 2017-03-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) / Neste trabalho propõe-se o desenvolvimento de uma ferramenta computacional para o planejamento da operação de curto prazo de sistemas de distribuição com geração distribuída (GD) considerando uma abordagem probabilística. Uma modelagem sequencial formulada com base na perspectiva das companhias de distribuição (DisCos) é proposta. As decisões operacionais da DisCo são inicialmente otimizadas no estágio de operação day-ahead (DA) e, então, na operação real-time (RT). A operação DA visa maximizar a diferença entre a energia vendida aos consumidores e as compras realizadas no mercado de eletricidade atacadista e da GD, ou seja, os lucros. No estágio RT, busca-se a minimização dos ajustes necessários para acomodar os desvios das quantidades previstas no planejamento DA. Modelos de cargas dependentes de tensão e restrições relacionadas à demanda são explicitamente formulados. A rede é representada através de equações de fluxo de potência AC completo. Propõe-se ainda a incorporação de um mecanismo para precificação nodal de potência reativa. Os modelos resultantes são caracterizados como programas de otimização matemática multiperíodo de grande porte não lineares e não convexos com variáveis contínuas e discretas. Um algoritmo pseudodinâmico baseado na meta-heurística Busca Tabu (BT) é proposto para solução do problema resultante de maneira eficaz, sem linearizações. Os resultados obtidos para alimentadores de distribuição de 69 e 135 barras ilustram a eficiência da metodologia proposta. / In this work, we propose a solution solution procedure for the short-term operation planning of distribution systems with distributed generation (DG) considering a probabilistic approach. A sequential formulation based on the distribution company's (DisCo's) perspective is presented. The DisCo’s operational decisions are optimized first in a day-ahead (DA) operation stage, and then in real-time (RT). The DA operation maximizes the difference between the energy sold to customers and the purchases from the wholesale electricity market and distributed generators. In RT, the objective is to minimize the adjustments that are required to accommodate deviations from forecasted quantities. The voltage-sensitiveness of power load injections and demand related constraints are explicitly formulated. The network is modeled using full ac power flow equations. In addition, a nodal-based reactive power pricing mechanism is proposed to be incorporated in the formulation. The resulting models are characterized as large-scale non-linear non-convex mathematical programs with continuous and discrete variables. A pseudo-dynamic Tabu Search (TS)-based solution algorithm is used to tackle the problem in an effective manner, without linearizations. Numerical results from the 69-bus and 135-bus distribution test feeders illustrate the performance of the proposed approach. / FAPESP: 2013/13070-7 / FAPESP: 2014/22314-0

Orientador: José Roberto Sanches Mantovani / Resumo: Os modernos sistemas aéreos de distribuição de energia elétrica são projetados para operar com altos índices de confiabilidade. Todavia, interrupções de fornecimento podem ocorrer a qualquer momento e causadas pelos mais diversos fatores, tais como, vendavais, árvores, ou ainda, colisão de veículos com a rede. Portanto, para garantir o mínimo impacto destas interrupções nos índices de confiabilidade da rede, áreas sem fornecimento devem ser reenergizadas tão rá- pido quanto possível. Este processo de reenergização do sistema é comumente denominado restauração. O principal objetivo do processo de restauração é restabelecer o maior número de cargas, no menor intervalo de tempo possível, por meio de uma sequência de aberturas e fechamentos de chaves de manobras. A existência de um conjunto de chaves seccionadoras estrategicamente posicionadas na rede permite que a estrutura malhada dos sistemas de distribuição opere com topologias radiais. Portanto, a execução de uma sequência de manobras é capaz de alterar a topologia radial da rede e restabelecer as cargas previamente sem fornecimento de energia. Este trabalho propõe uma nova metodologia para solução do problema de restauração de sistemas de distribuição de energia elétrica baseado no uso conjunto da meta-heurística de busca tabu, a representação nó-profundidade (RNP) e seus operadores PAO e CAO. Os operadores da RNP são empregados para originar a vizinhança da meta-heurística de busca tabu. Um novo operador foi introduzido e ... (Resumo completo, clicar acesso eletrônico abaixo) / Doutor

Cette thèse comporte deux parties majeures : la première partie est dédiée à l'étude du problème sparse CARP déterministe où nous avons développé une transformation du sparse CARP en un sparse CVRP. La seconde est consacrée au problème sparse CARP avec coûts sous incertitude. Nous avons donné une formulation mathématique du problème en min-max. Cette modélisation a permis d'identifier le pire scénario pour le problème robuste. Deux approches algorithmiques ont été proposées pour une résolution approchée. / This dissertation consists of two main parts : in the first part, we study the detreministic capacitated arc routing problem over sparse underlying graphs wher we have developed a new transformation techniquevof sparse CARP into sparse CVRP. The second part is consecrated about the sparse CARP with travel costs uncertainty. We have given a mathematical formulation of the probleme in min-max. A worst scenario for the robust problem is then identified, and two algorithmic approaches are proposed to determine a solution of the studied problem.

The thesis studies selected evolution systems to use in planning of high intensity focused ultrasound surgeries. Considered algorithms are statistically analyzed and compared by appropriate criteria to find the one that adds the most value to the potential real world medical problems.

First part of the thesis is about literature research of optimization algorithms. Three of the algorithms were implemented and tested, concretely the ant colony algorithm, tabu search and simulated annealing. All three algorithms were implemented to solve the traveling salesman problem. In second part of the thesis the algorithms were tested and compared. In last part the influence of the ant colony parameters was evaluated.

This thesis devote itself to use of information system for school agenda administration. Schools are forced to administer big amounts of informations, not only referred to their students. Broad issue is very extensive and disparate, so the most common types of data and demands on school information system operation are stated. The system for automatic generation of timetables is part of the school information system. At the first, basic conceptions of scheduling scope are defined and tied together with them are methods and algorithms for timetable creation problem solving. School timetabling is problem of scheduling lessons with certain limitative conditions. Further, thesis is engaged in design of school information system, data organization in such system and solving of system design problems. Designed information system accentuates on easy expandability and wide range of usage possibilities. Also suggested algorithm for solving of defined school timetabling is stated in this part of thesis.

Worldwide globalization has made supply chains more vulnerable to risk factors, increasing the associated costs of outsourcing goods. Outsourcing is highly beneficial for any company that values building upon its core competencies, but the emergence of the COVID-19 pandemic and other crises have exposed significant vulnerabilities within supply chains. These disruptions forced a shift in the production of goods from outsourcing to domestic methods. This paper considers a multi-echelon supply chain model with global and domestic raw material suppliers, manufacturing plants, warehouses, and markets. All levels within the supply chain network are evaluated from a holistic perspective, calculating a total cost for all levels with embedded risk. We formulate the problem as a mixed-integer linear model programmed in Excel Solver linear to solve smaller optimization problems. Then, we create a Tabu Search algorithm that solves problems of any size. Excel Solver considers three small-scale supply chain networks of varying sizes, one of which maximizes the decision variables the software can handle. In comparison, the Tabu Search program, programmed in Python, solves an additional ten larger-scaled supply chain networks. Tabu Search’s capabilities illustrate its scalability and replicability. A quadratic multi-regression analysis interprets the input parameters (iterations, neighbors, and tabu list size) associated with total supply chain cost and run time. The analysis shows iterations and neighbors to minimize total supply chain cost, while the interaction between iterations x neighbors increases the run time exponentially. Therefore, increasing the number of iterations and neighbors will increase run time but provide a more optimal result for total supply chain cost. Tabu Search’s input parameters should be set high in almost every practical case to achieve the most optimal result. This work is the first to incorporate risk and outsourcing into a multi-echelon supply chain, solved using an exact (Excel Solver) and metaheuristic (Tabu Search) solution methodology. From a practical case, managers can visualize supply chain networks of any size and variation to estimate the total supply chain cost in a relatively short time. Supply chain managers can identify suppliers and pick specific suppliers based on cost or risk. Lastly, they can adjust for risk according to external or internal risk factors. Future research directions include expanding or simplifying the supply chain network design, considering multiple parts, and considering scrap or defective products. In addition, one could incorporate a multi-product dynamic planning horizon supply chain. Overall, considering a hybrid method combining Tabu Search with genetic algorithms, particle swarm optimization, simulated annealing, CPLEX, GUROBI, or LINGO, could provide better results in a faster computational time.

Les services de livraison express font face au défi d’optimiser les routes de leurs véhicules alors que ceux-ci circulent dans un réseau routier où les temps de parcours varient en fonction du moment de la journée et où ils doivent répondre à l’arrivée dynamique de requêtes consistant à récupérer et livrer des colis. Notre but ici est de proposer une modélisation et une méthode de type heuristique pour résoudre ce problème. Nous commençons par explorer les travaux menés précédemment au sujet de l’arrivée dynamique des requêtes, des temps de parcours variables selon le moment de la journée et des collectes et livraisons dans les problèmes de tournées de véhicules. Ensuite, nous décrivons le problème de manière formelle sur le graphe du réseau routier avec des requêtes deux-points où l’objectif est de minimiser le temps total de parcours des véhicules et les temps de retard aux points de service et au dépôt. Par la suite, nous détaillons l’implémentation d’une méthode de résolution basée sur la recherche tabou utilisant une structure de voisinage basée sur la réinsertion d’une requête. Cette méthode utilise également la structure Dominant Shortest Path (DSP) qui considère plusieurs chemins alternatifs entre chaque paire de sommets, contrairement à l’approche traditionnelle où un chemin unique est fixé a priori. Finalement, nous testons notre méthode à l’aide de 390 instances générées de manière synthétique afin d’évaluer son efficacité ainsi que l’impact de certains aspects du problème et de la méthode de résolution. Les résultats démontrent une amélioration particulièrement importante due à l’utilisation de la structure DSP. / Express delivery services face the challenge of optimizing the routes of their vehicles while they are moving in a road network where the travel times vary according to the time of day in order to serve dynamic requests which consist in collecting and delivering parcels. Our goal here is to propose a model and a heuristic method to solve this problem. We begin by exploring previous work on the topic of the dynamic arrival of requests, timedependent travel times and pickups and deliveries in vehicle routing problems. Afterwards, we describe the problem formally on the graph of the road network with the objective of minimizing the total travel time of the vehicles and lateness at the service points and at the depot. Then, we detail the implementation of a solving method based on tabu search using a neighbourhood structure based on the reinsertion of a request. This method also uses the Dominant Shortest Path (DSP) structure which considers multiple alternative paths between each pair of vertices, unlike the traditional approach where a single path is fixed a priori. Finally, we test our method using 390 instances generated synthetically in order to evaluate its efficiency as well as the impact of certain aspects of the problem and solution method. The results show a particularly significant improvement due to the use of the DSP structure.

The Master Thesis deals with logistic module innovation of information system ERP. The principle of innovation is based on implementation of heuristic algorithms which solve Travel Salesman Problems (TSP). The software MATLAB is used for analysis and tests of these algorithms. The goal of Master Thesis is the comparison of selections algorithm, which are suitable for economic purposes (accuracy of solution, speed of calculation and memory demands).