Maximum Subarray Problem (MSP) is to find the consecutive array portion that maximizes the sum of array elements in it. The goal is to locate the most useful and informative array segment that associates two parameters involved in data in a 2D array. It's an efficient data mining method which gives us an accurate pattern or trend of data with respect to some associated parameters. Distance Matrix Multiplication (DMM) is at the core of MSP. Also DMM and MSP have the worst-case complexity of the same order. So if we improve the algorithm for DMM that would also trigger the improvement of MSP. The complexity of Conventional DMM is O(n³). In the average case, All Pairs Shortest Path (APSP) Problem can be modified as a fast engine for DMM and can be solved in O(n² log n) expected time. Using this result, MSP can be solved in O(n² log² n) expected time. MSP can be extended to K-MSP. To incorporate DMM into K-MSP, DMM needs to be extended to K-DMM as well. In this research we show how DMM can be extended to K-DMM using K-Tuple Approach to solve K-MSP in O(Kn² log² n log K) time complexity when K ≤ n/log n. We also present Tournament Approach which solves K-MSP in O(n² log² n + Kn²) time complexity and outperforms the K-Tuple

Cette thèse porte sur le problème de l'estimation des temps de parcours, de véhicules, par section de route dans un contexte urbain, en utilisant les données GPS à faible densité d’échantillon. L'un des défis de cette thèse est d'utiliser ce genre de données. Dans le cadre de ce travail de recherche, j'ai développé une carte numérique avec son nouveau système d'information géographique (SIG), qui traite la problématique du map-matching, où nous avons apporté des améliorations, ainsi que le problème du plus court chemin.La thèse s'inscrit dans le cadre du projet PUMAS (Plate-forme Urbaine de Mobilité Avancée et Soutenable), ce qui est un avantage pour nos recherches en ce qui concerne le processus de collecte de données réelles sur le terrain ainsi que pour faire nos tests. Le projet PUMAS est un projet préindustriel qui a pour objectif d'informer sur la situation du trafic mais également de développer et de mettre en œuvre une plate-forme de mobilité durable afin de l'évaluer dans la région, notamment à Rouen, France. Le résultat offre un cadre pour tout contrôleur de la situation, gestionnaire ou chercheur pour accéder à de vastes réserves de données sur l'estimation du flux du trafic, sur les prévisions et sur l'état du trafic. / This dissertation is concerned with the problem of estimating travel time per links in urban context using sparsely sampled GPS data. One of the challenges in this thesis is use the sparsely sampled data. A part of this research work, i developed a digital map with its new geographic information system (GIS), dealing with map-matching problem, where we come out with an enhancement tecnique, and also the shortest path problem.The thesis research work was conduct within the project PUMAS, which is an avantage for our research regarding the collection process of our data from the real world field and also in making our tests. The project PUMAS (Plate-forme Urbaine de Mobilité Avancée et Soutenable / Urban Platform for Sustainable and Advanced Mobility) is a preindustrial project that has the objective to inform about the traffic situation and also to develop an implement a platform for sustainable mobility in order to evaluate it in the region, specifically Rouen, France. The result is a framework for any traffic controller or manager and also estimation researcher to access vast stores of data about the traffic estimation, forecasting and status.

Devido a restrições de aplicabilidade presentes nos algoritmos para a solução de problemas de otimização combinatória, os sistemas baseados em redes neurais artificiais e algoritmos genéticos oferecem um método alternativo para solucionar tais problemas eficientemente. Os algoritmos genéticos devem a sua popularidade à possibilidade de percorrer espaços de busca não-lineares e extensos. Já as redes neurais artificiais possuem altas taxas de processamento por utilizarem um número elevado de elementos processadores simples com alta conectividade entre si. Complementarmente, redes neurais com conexões realimentadas fornecem um modelo computacional capaz de resolver vários tipos de problemas de otimização, os quais consistem, geralmente, da otimização de uma função objetivo que pode estar sujeita ou não a um conjunto de restrições. Esta tese apresenta uma abordagem inovadora para resolver problemas de conexão em otimização combinatória utilizando uma arquitetura neuro-genética. Mais especificamente, uma rede neural de Hopfield modificada é associada a um algoritmo genético visando garantir a convergência da rede em direção aos pontos de equilíbrio factíveis que representam as soluções para os problemas de otimização combinatória. / Due to applicability constraints involved with the algorithms for solving combinatorial optimization problems, systems based on artificial neural networks and genetic algorithms are alternative methods for solving these problems in an efficient way. The genetic algorithms must its popularity to make possible cover nonlinear and extensive search spaces. On the other hand, artificial neural networks have high processing rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Additionally, neural networks with feedback connections provide a computing model capable of solving a large class of optimization problems, which refer to optimization of an objective function that can be subject to constraints. This thesis presents a novel approach for solving connection problems in combinatorial optimization using a neurogenetic approach. More specifically, a modified Hopfield neural network is associated with a genetic algorithm in order to guarantee the convergence of the network to the equilibrium points, which represent feasible solutions for the combinatorial optimization problems.

Submitted by William Justo Figueiro (williamjf) on 2015-07-21T22:37:51Z No. of bitstreams: 1 63c.pdf: 2699232 bytes, checksum: 1ae2013ef31101508f9fef3997d71790 (MD5) / Made available in DSpace on 2015-07-21T22:37:51Z (GMT). No. of bitstreams: 1 63c.pdf: 2699232 bytes, checksum: 1ae2013ef31101508f9fef3997d71790 (MD5) Previous issue date: 2013 / SIMTUR - Sistema Inteligente De Monitoramento de Tráfego Urbano / O crescente aumento do uso de automóveis e de motocicletas tem provocado uma contínua degradação no trânsito urbano das grandes metrópoles. Este cenário é agravado pelas deficiências nos atuais sistemas de transporte público, geradas, em parte, pela falta de informação ao usuário. O presente trabalho apresenta um modelo computacional para um sistema de informação ao usuário de transporte público. Ao contrário de outros trabalhos baseados no algoritmo clássico Dijkstra, a abordagem apresentada faz uso do algoritmo A* para resolução do problema de caminhos mínimos, presente neste contexto, a fim de reduzir o tempo de resposta de maneira que o modelo possa ser utilizado em um sistema real de informação ao usuário. O modelo proposto considera múltiplos critérios de decisão, como a distância total percorrida e o número de transbordos. Um estudo de caso foi realizado utilizando dados reais do transporte público da cidade Porto Alegre com o objetivo de avaliar o modelo computacional desenvolvido. Os resultados gerados foram comparados com aqueles obtidos através do emprego do algoritmo Dijkstra e indicam que a combinação do algoritmo A* com técnicas de aceleração permite reduzir, significativamente, a complexidade de espaço, o tempo de processamento e o número de transbordos. / The increasing use of automobiles and motorcycles has caused a continuous degradation in the traffic of large cities. This scenario gets worse due to shortcomings in the current public transportation, which is entailed, in a certain way, by the lack of information provided to the user. This study shows a computing model for a public transportation user information system. Unlike other studies based on the classical Dijkstra’s algorithm, the approach makes use of the algorithm A* to solve a shortest path problem to reduce the response time so that the model can be used in an real-time web information system. The proposed model takes into account multiple criteria of decision, such as total distance traveled and number of transfers and it was evaluated with data from Porto Alegre’s public transportation. The results were compared to those ones obtained by the use of Dijkstra’s algorithm and indicate that the combination of algorithm A* with acceleration techniques allows reducing significantly the space complexity, processing time and the number of transfers.

L'objectif de ce travail de thèse est de proposer des approches algorithmiques permettant de traiter la problématique du routage adaptatif (RA) dans un réseau de communication à trafic irrégulier. L'analyse des algorithmes existants nous a conduit à retenir comme base de travail l'algorithme Q-Routing (QR); celui-ci s'appuie sur la technique d'apprentissage par renforcement basée sur les modèles de Markov. L'efficacité de ce type de routage dépend fortement des informations sur la charge et la nature du trafic sur le réseau. Ces dernières doivent être à la fois, suffisantes, pertinentes et reflétant la charge réelle du réseau lors de la phase de prise de décision. Pour remédier aux inconvénients des techniques utilisant le QR, nous avons proposé deux algorithmes de RA. Le premier, appelé Q-Neural Routing, s'appuie sur un modèle neuronal stochastique pour estimer et mettre à jour les paramètres nécessaires au RA. Afin d'accélérer le temps de convergence, une deuxième approche est proposée : K-Shortest path Q-Routing. Elle est basée sur la technique de routage multi chemin combiné avec l'algorithme QR, l'espace d'exploration étant réduit aux k meilleurs chemins. Les deux algorithmes proposés sont validés et comparés aux approches traditionnelles en utilisant la plateforme de simulation OPNET, leur efficacité au niveau du RA est mise particulièrement en évidence. En effet, ceux-ci permettent une meilleure prise en compte de l'état du réseau contrairement aux approches classiques.

Devido a restrições de aplicabilidade presentes nos algoritmos para a solução de problemas de otimização combinatória, os sistemas baseados em redes neurais artificiais e algoritmos genéticos oferecem um método alternativo para solucionar tais problemas eficientemente. Os algoritmos genéticos devem a sua popularidade à possibilidade de percorrer espaços de busca não-lineares e extensos. Já as redes neurais artificiais possuem altas taxas de processamento por utilizarem um número elevado de elementos processadores simples com alta conectividade entre si. Complementarmente, redes neurais com conexões realimentadas fornecem um modelo computacional capaz de resolver vários tipos de problemas de otimização, os quais consistem, geralmente, da otimização de uma função objetivo que pode estar sujeita ou não a um conjunto de restrições. Esta tese apresenta uma abordagem inovadora para resolver problemas de conexão em otimização combinatória utilizando uma arquitetura neuro-genética. Mais especificamente, uma rede neural de Hopfield modificada é associada a um algoritmo genético visando garantir a convergência da rede em direção aos pontos de equilíbrio factíveis que representam as soluções para os problemas de otimização combinatória. / Due to applicability constraints involved with the algorithms for solving combinatorial optimization problems, systems based on artificial neural networks and genetic algorithms are alternative methods for solving these problems in an efficient way. The genetic algorithms must its popularity to make possible cover nonlinear and extensive search spaces. On the other hand, artificial neural networks have high processing rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. Additionally, neural networks with feedback connections provide a computing model capable of solving a large class of optimization problems, which refer to optimization of an objective function that can be subject to constraints. This thesis presents a novel approach for solving connection problems in combinatorial optimization using a neurogenetic approach. More specifically, a modified Hopfield neural network is associated with a genetic algorithm in order to guarantee the convergence of the network to the equilibrium points, which represent feasible solutions for the combinatorial optimization problems.

Les travaux présentés dans cette thèse, qui s’inscrivent dans le cadre du projet franco-allemand DSS_Evac_Logistic, visent à proposer des méthodes permettant de calculer des plans d’évacuation macroscopiques d’une ville lors d’une catastrophe majeure. Deux problèmes d’évacuations sont considérés dans cette thèse : le problème d’évacuation par bus et le problème d’évacuation par bus et voitures. Le problème d’évacuation par bus a pour objectif de définir un plan d’évacuation afin de mettre à l’abri les évacués. Dans cette thèse, nous nous sommes intéressés à l’étude de trois versions du problème d’évacuation par bus. La première version est monocritère où nous cherchons à minimiser la date de fin d’évacuation. Puis, dans le second problème et afin d’assurer la sécurité des évacués, nous avons considéré une version bicritère qui généralise le cas monocritère, en incluant le risque encouru lors de l’évacuation des personnes. Les deux critères à minimiser sont la date de fin d’évacuation et le risque. La troisième version est une version robuste bicritère qui permet d’appréhender l’incertitude sur les données. Le but est de minimiser à la fois la date de fin d’évacuation et les modifications apportées sur une solution, de sorte qu’elle soit réalisable pour n’importe quel scénario de données. Pour résoudre ces problèmes d’évacuation par bus, nous avons proposé des méthodes exactes et des méthodes heuristiques. / The work presented in this thesis, which is a part of the Franco-German project DSS_Evac_Logistic, aims at proposing methods to calculate macroscopic evacuation plans for mid-size towns after a tremendous disaster. Two evacuation problems have been tackled in this thesis : the bus evacuation problem and bus-and-vehicle evacuation problem. The bus evacuation problem aims at calculating an evacuation plan to relocate evacuees outside the endangered area. In this thesis, we consider three versions of the bus evacuation problem. The first one is a monocriterion problem, where the objective is to minimize the maximum evacuation time. In order to guarantee the safety of evacuees, we have considered a bicriteria problem, which is a generalization of the monocriterion version, in which we take into consideration the risk exposure of the evacuees. Consequently, the bicriteria problem is solved by minimizing the total evacuation time and the risk. The third version is a bicriteria robust version because most of the planning data is subject to uncertainty. The goal is to minimize both the evacuation time and the vulnerability of the schedule that is subject to different evacuation circumstances. To solve all the versions of the bus evacuation problem, we have developed exact solutions based on mathematical formulation to address small instances and heuristic solutions to deal with larger instances.

Made available in DSpace on 2016-08-31T13:33:41Z (GMT). No. of bitstreams: 1 TarcisioSB_DISSERT.pdf: 1571314 bytes, checksum: 86e8646fa8da6455187767e219181490 (MD5) Previous issue date: 2014-12-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Studies on connections lock in computer networks have been gaining prominence in recent research focused on computational communication and technology. Several researchers have used various methods in order to identify and minimize the blocking rate that prevent a connection is established. This paper presents a blocking rate analysis in connections of shortest paths algorithms. They have on the performance of a transparent optical network. Two algorithms will be used to perform the analysis and simulations, the Genetic Algorithm (AG) and the algorithm Yen (AY). The Genetic Algorithm is based on Computational Intelligence (CI) and the Yen algorithm is based on the principle of finding and identifying the K shortest paths. Numerical simulations performed on different network scenarios show that the greater the number of connections, the higher the blocking rate in the connections. This study will help to identify which algorithm behaves better in the specific cases described in this work / Os estudos sobre bloqueio de conexões em redes de computadores vêm ganhando destaque em recentes pesquisas voltadas à comunicação computacional e tecnologia. Vários pesquisadores têm utilizado diversos métodos buscando identificar e minimizar ao máximo a taxa média de bloqueio que impedem que uma conexão seja estabelecida. Este trabalho apresenta uma análise de taxa média de bloqueio em conexões por algoritmos de caminhos mínimos. Têm sobre o desempenho de uma rede ótica transparente. Serão utilizados dois algoritmos para realizar a análise e as simulações, o Algoritmo Genético (AG) e o Algoritmo de Yen (AY). O Algoritmo Genético fundamentado por Inteligência Computacional (IC) e o Algoritmo de Yen baseado no princípio de encontrar e identificar os K menores caminhos. Simulações numéricas realizadas em diferentes cenários da rede mostram que, quanto maior o número de conexões, maior será a taxa média de bloqueio nas conexões. Através desse estudo será possível identificar qual algoritmo se comporta melhor para os casos específicos descritos nesse trabalho

This dissertation investigates in which conditions the optimal configuration of an electric power network is a minimum length spanning tree, and in which conditions it is shortest path tree configuration. For this purpose the dissertation, it applies computational optimization mathematical models of an optimal local access network design problem. The focus of the study is the 13.8 kV spacer cable primary radial networks. Applied models seek for the balance betweenfixedcostsandvariablecosts.Savedvaluesfromanoptimalnetworkcouldbeapplied to increase the range of the network and people reached as well. The bibliographic research is compound by three parts: graph theory, local access network optimization models, and distribution network costs. Research methodology includes the choice of the distribution system, determination of fixed and variable costs, choice and implementation of the local access network optimization models, tests in hypothetical and realistic systems by using the CPLEX solver, analysis of the resulting configuration, and construction of graphics to facilitate the results evaluation. It was found that the relationship between fixed costs and variable costs influences the optimal configuration of the distribution network in such a way that a low value of the quotient between fixed costs and variable costs contributes to a shortest path tree. On the other hand, a high quotient between fixed costs and variable costs contributes to a minimum length spanning tree configuration. However, others parameters must be considered to determine the network configuration such as extension, arches demand and quantity of arches. / O presente trabalho visa investigar sob quais condições a configuração ótima de uma rede de distribuição elétrica é uma árvore geradora mínima (AGM) e sob quais é uma árvore de caminhos mínimos (ACM). Utilizando, para isso, modelos matemáticos computacionais de otimização topológica de redes de utilidade pública. As redes de distribuição estudadas foram do tipo aérea radial primária protegida (ARPP) com nível de tensão em 13,8 kV. Os modelos utilizados prezam pelo equilíbrio entre o custo de investimento inicial (fixo) e os custos decorrentes da transferência de energia elétrica (variável). Os valores economizados através de uma configuração ótima da rede podem ser convertidos em investimentos para aumentar o número de pessoas com acesso aos recursos energéticos com eficiência e qualidade. A revisão bibliográfica foi dividida em três partes: teoria dos grafos, modelos de otimização de redes de acesso local e custos de redes de distribuição. A metodologia utilizada compreendeu as seguintes etapas: escolha do tipo de sistema de distribuição, determinação dos custos fixo e variável, escolha e implementação (GAMS) dos modelos, testes com exemplos de redes usando o solver CPLEX, análise das configurações resultantes e elaboração de gráficos para facilitar a avaliação dos resultados. Os resultados mostraram que a relação entre o custo fixo β e o custo variável γ exerce influência determinante na configuração ótima de uma rede de distribuição ARPP. Um valor baixo de β/γ, favorece a ACM. Já valores elevados de β/γ, conduzem a solução para uma AGM. No entanto, essa relação não é o único fator que determina a configuração da rede, outros parâmetros como extensão, demanda dos nós e quantidade de possíveis arcos influenciam de forma significativa na solução apresentada.

abstract: Optimization of on-demand transportation systems and ride-sharing services involves solving a class of complex vehicle routing problems with pickup and delivery with time windows (VRPPDTW). Previous research has made a number of important contributions to the challenging pickup and delivery problem along different formulation or solution approaches. However, there are a number of modeling and algorithmic challenges for a large-scale deployment of a vehicle routing and scheduling algorithm, especially for regional networks with various road capacity and traffic delay constraints on freeway bottlenecks and signal timing on urban streets. The main thrust of this research is constructing hyper-networks to implicitly impose complicated constraints of a vehicle routing problem (VRP) into the model within the network construction. This research introduces a new methodology based on hyper-networks to solve the very important vehicle routing problem for the case of generic ride-sharing problem. Then, the idea of hyper-networks is applied for (1) solving the pickup and delivery problem with synchronized transfers, (2) computing resource hyper-prisms for sustainable transportation planning in the field of time-geography, and (3) providing an integrated framework that fully captures the interactions between supply and demand dimensions of travel to model the implications of advanced technologies and mobility services on traveler behavior. / Dissertation/Thesis / Doctoral Dissertation Civil, Environmental and Sustainable Engineering 2018