926 resultados para Routing problems
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Thèse réalisée en cotutelle entre l'Université de Montréal et l'Université de Technologie de Troyes
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For routing problems in interconnection networks it is important to find the shortest containers between any two vertices, since the w-wide diameter gives the maximum communication delay when there are up to w−1 faulty nodes in a network modeled by a graph. The concept of ‘wide diameter’ was introduced by Hsu [41] to unify the concepts of diameter and The concept of ‘domination’ has attracted interest due to its wide applications in many real world situations [38]. A connected dominating set serves as a virtual backbone of a network and it is a set of vertices that helps in routing. In this thesis, we make an earnest attempt to study some of these notions in graph products. This include, the diameter variability, the diameter vulnerability, the component factors and the domination criticality.connectivity
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La optimización de sistemas y modelos se ha convertido en uno de los factores más importantes a la hora de buscar la mayor eficiencia de un proceso. Este concepto no es ajeno al transporte escolar, ambiente que cambia constantemente al ritmo de las necesidades de sus clientes, y que responde ante una fuerte responsabilidad frente a sus usuarios, los niños que hacen uso del servicio, en cuanto al cumplimiento de tiempos y seguridad, mientras busca constantemente la reducción de costos. Este proyecto expone las problemáticas presentadas en The English School en esta área y propone un modelo de optimización simple que permitirá notables mejoras en términos de tiempos y costos, de tal forma que genere beneficios para la institución en términos financieros y de satisfacción al cliente. Por medio de la implementación de este modelo será posible identificar errores comunes del proceso, se identificarán soluciones prácticas de fácil aplicación en el manejo del transporte y se presentarán los resultados obtenidos en la muestra utilizada para desarrollar el proyecto.
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This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.
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Worldwide, the demand for transportation services for persons with disabilities, the elderly, and persons with reduced mobility have increased in recent years. The population is aging, governments need to adapt to this reality, and this fact could mean business opportunities for companies. Within this context is inserted the Programa de Acessibilidade Especial porta a porta PRAE, a door to door public transportation service from the city of Natal-RN in Brazil. The research presented in this dissertation seeks to develop a programming model which can assist the process of decision making of managers of the shuttle. To that end, it was created an algorithm based on methods of generating approximate solutions known as heuristics. The purpose of the model is to increase the number of people served by the PRAE, given the available fleet, generating optimized schedules routes. The PRAE is a problem of vehicle routing and scheduling of dial-a-ride - DARP, the most complex type among the routing problems. The validation of the method of resolution was made by comparing the results derived by the model and the currently programming method. It is expected that the model is able to increase the current capacity of the service requests of transport
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Il lavoro di tesi svolto riguarda la progettazione e lo sviluppo di un algoritmo per la pianificazione ottimizzata della distribuzione con viaggi sincronizzati; il metodo sviluppato è un algoritmo mateuristico. I metodi mateuristici nascono dall’integrazione di algoritmi esatti, utilizzati all’interno di un framework metaeuristico, scelto come paradigma di soluzione del problema. La combinazione di componenti esatte e algoritmi metaeuristici ha lo scopo di sfruttare i vantaggi di entrambi gli approcci: grazie all'uso di componenti esatte, è possibile operare in modo efficace e di concentrarsi su alcuni dei vincoli del problema, mentre, con l'utilizzo di un framework metaeuristico, si può efficacemente esplorare grandi aree dello spazio di ricerca in tempi accettabili. Il problema analizzato nel lavoro di tesi è un problema di trasporto, ovvero il Vehicle Routing Problem con finestre temporali e vincoli di sincronizzazione a coppie (VRPTWPS). Il problema richiede di individuare un piano di organizzazione ottimizzato per i viaggi di consegna merci presso un insieme di clienti; ogni cliente richiede che la consegna avvenga all’interno di orari predefiniti; un sottoinsieme di essi richiede, inoltre, che la consegna venga effettuata con la presenza di esattamente due addetti. La presenza di quest’ultimo vincolo richiede, dunque, che due incaricati, indipendentemente dai viaggi di visita che questi effettuano, si incontrino presso uno stesso cliente nello stesso istante. Il vincolo di sincronizzazione rende il problema difficile da risolvere in maniera ottimizzata con i tradizionali metodi di ricerca locale; da ciò nasce l’uso dei metodi mateuristici per la risoluzione ottimizzata del problema. Grazie all’utilizzo di algoritmi esatti, i metodi mateuristici riescono a trattare in maniera più efficace alcuni vincoli dei problemi da risolvere.
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The goal of Vehicle Routing Problems (VRP) and their variations is to transport a set of orders with the minimum number of vehicles at least cost. Most approaches are designed to solve specific problem variations independently, whereas in real world applications, different constraints are handled concurrently. This research extends solutions obtained for the traveling salesman problem with time windows to a much wider class of route planning problems in logistics. The work describes a novel approach that: supports a heterogeneous fleet of vehicles dynamically reduces the number of vehicles respects individual capacity restrictions satisfies pickup and delivery constraints takes Hamiltonian paths (rather than cycles) The proposed approach uses Monte-Carlo Tree Search and in particular Nested Rollout Policy Adaptation. For the evaluation of the work, real data from the industry was obtained and tested and the results are reported.
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The rolling stock circulation depends on two different problems: the rolling stock assignment and the train routing problems, which up to now have been solved sequentially. We propose a new approach to obtain better and more robust circulations of the rolling stock train units, solving the rolling stock assignment while accounting for the train routing problem. Here robustness means that difficult shunting operations are selectively penalized and propagated delays together with the need for human resources are minimized. This new integrated approach provides a huge model. Then, we solve the integrated model using Benders decomposition, where the main decision is the rolling stock assignment and the train routing is in the second level. For computational reasons we propose a heuristic based on Benders decomposition. Computational experiments show how the current solution operated by RENFE (the main Spanish train operator) can be improved: more robust and efficient solutions are obtained
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores
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Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia Informática
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Verkkoon kytkettävien laitteiden määrä on lisääntynyt viime vuosina, joka luo tarpeen reitittimille ja niiden ominaisuuksille. On muodostunut uusi tarve laitteille, jotka voivat yhdistää erilaisia verkkoja toisiinsa. Tällaisen reitittimen rakentamiseen tarvitaan vakaa alusta. Tällaisella alustalla luodaan mahdollisuus kuormittaa järjestelmää ilman suuria ongelmia. Tällainen alusta on Open Platform, joka on suunniteltu tällaisille toiminnoille ja yhdessä oikeanlaisen verkkoratkaisun kanssa sitä voidaan käyttää sille suunnitellussa ympäristössä. Tämän diplomityön tarkoituksena on arvioida neljää eri reititysohjelmistoa ja kahta eri IP pinoa. Työssä käytetyt testit on suunniteltu arviointia varten ja niiden tarkoituksena on tuoda esille ohjelmistoissa esiintyvät viat ja ongelmat. Kaikki testit ovat samoja kaikille ohjelmille ja tehdään samassa ympäristössä. Testit analysoidaan niiden ajon jälkeen ja niiden tulosten avulla tehdään päätös mitä näistä ohjelmistoista tullaan käyttämään seuraavan sukupolven avoimella alustalla, joka tulee toimimaan Nokian Intelligent Service Nodessa. Tämä verkon laite toimii yhdyskäytävänäerilaisten verkkojen välillä.
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Wireless sensor networks monitor their surrounding environment for the occurrence of some anticipated phenomenon. Most of the research related to sensor networks considers the static deployment of sensor nodes. Mobility of sensor node can be considered as an extra dimension of complexity, which poses interesting and challenging problems. Node mobility is a very important aspect in the design of effective routing algorithm for mobile wireless networks. In this work we intent to present the impact of different mobility models on the performance of the wireless sensor networks. Routing characteristics of various routing protocols for ad-hoc network were studied considering different mobility models. Performance metrics such as end-to-end delay, throughput and routing load were considered and their variations in the case of mobility models like Freeway, RPGM were studied. This work will be useful to figure out the characteristics of routing protocols depending on the mobility patterns of sensors
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This Thesis Work will concentrate on a very interesting problem, the Vehicle Routing Problem (VRP). In this problem, customers or cities have to be visited and packages have to be transported to each of them, starting from a basis point on the map. The goal is to solve the transportation problem, to be able to deliver the packages-on time for the customers,-enough package for each Customer,-using the available resources- and – of course - to be so effective as it is possible.Although this problem seems to be very easy to solve with a small number of cities or customers, it is not. In this problem the algorithm have to face with several constraints, for example opening hours, package delivery times, truck capacities, etc. This makes this problem a so called Multi Constraint Optimization Problem (MCOP). What’s more, this problem is intractable with current amount of computational power which is available for most of us. As the number of customers grow, the calculations to be done grows exponential fast, because all constraints have to be solved for each customers and it should not be forgotten that the goal is to find a solution, what is best enough, before the time for the calculation is up. This problem is introduced in the first chapter: form its basics, the Traveling Salesman Problem, using some theoretical and mathematical background it is shown, why is it so hard to optimize this problem, and although it is so hard, and there is no best algorithm known for huge number of customers, why is it a worth to deal with it. Just think about a huge transportation company with ten thousands of trucks, millions of customers: how much money could be saved if we would know the optimal path for all our packages.Although there is no best algorithm is known for this kind of optimization problems, we are trying to give an acceptable solution for it in the second and third chapter, where two algorithms are described: the Genetic Algorithm and the Simulated Annealing. Both of them are based on obtaining the processes of nature and material science. These algorithms will hardly ever be able to find the best solution for the problem, but they are able to give a very good solution in special cases within acceptable calculation time.In these chapters (2nd and 3rd) the Genetic Algorithm and Simulated Annealing is described in details, from their basis in the “real world” through their terminology and finally the basic implementation of them. The work will put a stress on the limits of these algorithms, their advantages and disadvantages, and also the comparison of them to each other.Finally, after all of these theories are shown, a simulation will be executed on an artificial environment of the VRP, with both Simulated Annealing and Genetic Algorithm. They will both solve the same problem in the same environment and are going to be compared to each other. The environment and the implementation are also described here, so as the test results obtained.Finally the possible improvements of these algorithms are discussed, and the work will try to answer the “big” question, “Which algorithm is better?”, if this question even exists.
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A constraint satisfaction problem is a classical artificial intelligence paradigm characterized by a set of variables (each variable with an associated domain of possible values), and a set of constraints that specify relations among subsets of these variables. Solutions are assignments of values to all variables that satisfy all the constraints. Many real world problems may be modelled by means of constraints. The range of problems that can use this representation is very diverse and embraces areas like resource allocation, scheduling, timetabling or vehicle routing. Constraint programming is a form of declarative programming in the sense that instead of specifying a sequence of steps to execute, it relies on properties of the solutions to be found, which are explicitly defined by constraints. The idea of constraint programming is to solve problems by stating constraints which must be satisfied by the solutions. Constraint programming is based on specialized constraint solvers that take advantage of constraints to search for solutions. The success and popularity of complex problem solving tools can be greatly enhanced by the availability of friendly user interfaces. User interfaces cover two fundamental areas: receiving information from the user and communicating it to the system; and getting information from the system and deliver it to the user. Despite its potential impact, adequate user interfaces are uncommon in constraint programming in general. The main goal of this project is to develop a graphical user interface that allows to, intuitively, represent constraint satisfaction problems. The idea is to visually represent the variables of the problem, their domains and the problem constraints and enable the user to interact with an adequate constraint solver to process the constraints and compute the solutions. Moreover, the graphical interface should be capable of configure the solver’s parameters and present solutions in an appealing interactive way. As a proof of concept, the developed application – GraphicalConstraints – focus on continuous constraint programming, which deals with real valued variables and numerical constraints (equations and inequalities). RealPaver, a state-of-the-art solver in continuous domains, was used in the application. The graphical interface supports all stages of constraint processing, from the design of the constraint network to the presentation of the end feasible space solutions as 2D or 3D boxes.
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Multicommodity flow (MF) problems have a wide variety of applications in areas such as VLSI circuit design, network design, etc., and are therefore very well studied. The fractional MF problems are polynomial time solvable while integer versions are NP-complete. However, exact algorithms to solve the fractional MF problems have high computational complexity. Therefore approximation algorithms to solve the fractional MF problems have been explored in the literature to reduce their computational complexity. Using these approximation algorithms and the randomized rounding technique, polynomial time approximation algorithms have been explored in the literature. In the design of high-speed networks, such as optical wavelength division multiplexing (WDM) networks, providing survivability carries great significance. Survivability is the ability of the network to recover from failures. It further increases the complexity of network design and presents network designers with more formidable challenges. In this work we formulate the survivable versions of the MF problems. We build approximation algorithms for the survivable multicommodity flow (SMF) problems based on the framework of the approximation algorithms for the MF problems presented in [1] and [2]. We discuss applications of the SMF problems to solve survivable routing in capacitated networks.