The Capacitated Arc Routing Problem has many applications in real life. The aim of this problem is to minimize the total cost at fulfilment of the requirements of arcs. The Capacitated Arc Routing Problem is an extension of the Chinese Postman Problem, which is a special type of the Vehicle Routing Problems. In this thesis is explained the issue of the Chinese Postman Problem and its extensions at first. Subsequently the applications of mathematical models are illustrated on a model example. However these mathematical models, which are searching the optimal solution, do not use so much in reality. Therefore the randomized heuristic algorithm for solving these problems is suggested and programmed in this thesis. Subsequently this heuristic was applied to case study of garbage collection in Podebrady city.

Orientador: Paulo Morelato França / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-09T05:57:31Z (GMT). No. of bitstreams: 1 Usberti_FabioLuiz_M.pdf: 37565259 bytes, checksum: cddb8b852bd82318a8c784f1f223a076 (MD5) Previous issue date: 2007 / Resumo: Esse trabalho se dedicou ao estudo dos algoritmos para roteamento de leituristas, incluindo propostas de alteração que resultem na melhoria da qualidade dos resultados. A motivação é proveniente da alta demanda por soluções computacionais para esse problema, ainda pouco estudado devido às peculiaridades que lhe são inerentes. Encontram-se na literatura duas heurísticas, de estratégias distintas e antagônicas para esse problema. Uma das heurísticas procura construir a rota ignorando a restrição de capacidade, para posterior particionamento dessa rota em subrotas, cada qual destinada a um leiturista (¿route first, cluster second¿). A outra heurística, em uma abordagem inversa, primeiramente subdivide a região de trabalho dos leituristas, para posterior roteamento dessas partições (¿cluster first, route second¿). Essas duas heurísticas foram testadas exaustivamente, tornando possível localizar aspectos sujeitos à melhoria, dando origem a duas novas heurísticas. Foi gerada uma base de testes contendo 144 instâncias que simulam as condições reais de trabalho dos leituristas, classificadas de acordo com o tamanho e dificuldade. A partir das soluções provenientes dos quatro algoritmos foi possível analisá-los comparativamente, avaliando o melhor em um âmbito geral (envolvendo todos os algoritmos) e específico (algoritmos de mesmo tipo, ¿route first cluster second¿ ou ¿cluster first route second¿), segundo critérios de qualidade pré-definidos: número de rotas, tempo de percurso, violação da carga horária e tempo computacional. Os resultados revelam que os novos algoritmos foram melhores tanto na comparação específica quanto na comparação geral / Abstract: This work¿s main study object consists on algorithms for routing meter readers, from which proposals towards solution¿s improvement are made. The demand for computational results concerning this problem, added to literature little attention due to its inherited peculiarities, has been the outmost motivation. Two preexisting heuristics from literature, with distinct and antagonic strategies, are pointed out. One of these heuristics atempt to create a single route, dismissing the capacity restriction, and then partitionates this route into subroutes, each of them destinated to one meter reader (route first, cluster second). The other heuristic, in an inverse approach, first splits the meter reader¿s working area, and only then routes each of these partitions (cluster first, route second). The two heuristics were tested to exaustion, allowing enumeration of weak aspects subject to improvement. Therefore, two new heuristics were developed, based upon the originals, however adapted in order to outperform solution¿s quality. A testing base containing 144 instances was generated, simulating meter readers realistic labor¿s conditions, classified by size and difficulty. Through solutions provided by the four algorithms, comparison analyses have taken place, evaluating in a general (involving all algorithms) and specific manner (same kind algorithms, i.e., route first, cluster second or cluster first, route second), considering four predefined quality criteria: number of routes, deadheading time, violation of shiftwork time and computational time. Results revealed that the new algorithms achieved better solutions on specific and general comparisons / Mestrado / Automação / Mestre em Engenharia Elétrica

This work focuses on path planning for an autonomous UAV to tour and cover multiple regions in the shortest time. The three challenges to be solved are - finding the right optimal order to tour the neighborhoods, determining entry and exit points to neighborhoods, and covering each neighborhood. Two approaches have been explored and compared to achieve this goal - a TSP - Greedy and TSP - Dijkstra's. Both of them use a TSP solution to determine the optimal order of touring. They also use the same back and forth motion to cover each region. However, while the first approach uses a brute force to determine the the next closest node of entry or exit, the second approach utilizes the Dijkstra's algorithm to compute all possible paths to every node in the graph, and therefore choose the shortest pairs of entry and exit for each region, that would generate the shorter path, overall. The main contribution of this work is to implement an existing algorithm to combine the touring and covering problem, and propose a new algorithm to perform the same. Empirical results comparing performances of both approaches are included. Hardware experiments are performed on a spraying hexacopter, using the TSP - Greedy approach. Unique system characteristics are studied to make conclusions about stability of the platform. Future directions are identified to improve both software and hardware performance. / Master of Science / In a world with a rapidly growing population and resources depleting faster, increasing efficiency and productivity has become paramount. Until now, automation has helped cope with the world’s increasing demand for food. However, studies have shown that automation in itself will be insufficient in improving crop output in the coming years. Fortunately, another technology that is taking big leaps in terms of technological advances - Information Technology, when combined with automation, presents itself as a viable option. This takes agriculture towards a site-specific approach for all crop monitoring, growth and protection activities and is know as Precision Agriculture. Spraying fluids on crops using a UAV is on of the prominent problems being researched in this field. This work presents two approaches - TSP - Greedy and TSP - Dijkstra’s to tour or visit and spray multiple regions that have been previously identified in the shortest time. While the TSP - Greedy algorithm is an implementation of an existing approach, the TSP - Dijkstra’s algorithm is a new approach proposed in this work. The solution to TSP or Traveling Salesman Problem generates the optimal order to visit the regions. The ’Greedy’ or ’Dijsktra’s’ approaches define entry and exit points for each region, that gives the shortest path overall. Images of areas with weed afflicted regions marked on them are used as the input for this algorithm. The TSP-Greedy approach is used in performing hardware experiments. Data collected from these experiments are used to analyze performance of an Unmanned Aerial Vehicle (UAV) platform. Water has been used as the spraying fluid for testing the sprayer assembly. GPS or Global Positioning System is used for navigation of the UAV. Future directions are identified to improve both software and hardware performance.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal.

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

A operação de coleta e transporte de resíduos sólidos urbanos é indispensável dentro de quaisquer sistema de limpeza urbana. É necessário que se intensifique a pesquisa nessa área de conhecimento afim de produzir-se material de auxílio ao poder público municipal e o setor privado. Deste modo o objetivo geral deste trabalho é o estudo da utilização de ferramentas computacionais para a otimização dos roteiros dos serviços de coleta de resíduos sólidos domiciliares. Foi feito um comparativo entre os itinerários percorridos pelos caminhões de coleta quando dimensionados de forma empírica e quando dimensionados com o auxílio de ferramentas computacionais. Verificou-se as vantagens e desvantagens de cada modelo de dimensionamento e o grande potencial de redução de custos quando utilizadas ferramentas computacionais. / The operation of collection and transportation of municipal solid waste is essential within any system of urban sanitation. It is necessary to intensify research in this area of knowledge in order to produce up to aid the municipal government and the private sector material. Thus the objective of this work is to study the use of computational tools for the optimization of routes of solid waste collection services. A comparison between the routes traveled by pickup truck when scaled empirically and when scaled with the aid of computational tools was made. There are advantages and disadvantages of each model sizing and great potential for cost savings when used computational tools.

A operação de coleta e transporte de resíduos sólidos urbanos é indispensável dentro de quaisquer sistema de limpeza urbana. É necessário que se intensifique a pesquisa nessa área de conhecimento afim de produzir-se material de auxílio ao poder público municipal e o setor privado. Deste modo o objetivo geral deste trabalho é o estudo da utilização de ferramentas computacionais para a otimização dos roteiros dos serviços de coleta de resíduos sólidos domiciliares. Foi feito um comparativo entre os itinerários percorridos pelos caminhões de coleta quando dimensionados de forma empírica e quando dimensionados com o auxílio de ferramentas computacionais. Verificou-se as vantagens e desvantagens de cada modelo de dimensionamento e o grande potencial de redução de custos quando utilizadas ferramentas computacionais. / The operation of collection and transportation of municipal solid waste is essential within any system of urban sanitation. It is necessary to intensify research in this area of knowledge in order to produce up to aid the municipal government and the private sector material. Thus the objective of this work is to study the use of computational tools for the optimization of routes of solid waste collection services. A comparison between the routes traveled by pickup truck when scaled empirically and when scaled with the aid of computational tools was made. There are advantages and disadvantages of each model sizing and great potential for cost savings when used computational tools.

This master's thesis deals with mathematical model building for routing problems and ways to solve them. There are discussed and implemented deterministic and heuristic approaches that are suitable to be utilized. A big effort is put into building of the mathematical model describing a real world problem from the field of waste management. Appropriate algorithms are developed and modified to solve a particular problem effectively. An original graphical environment is created to illustrate acquired results and perform testing computations.

Le problème de tournées de véhicules est un des problèmes d’optimisation combinatoire les plus connus et les plus difficiles. Il s’agit de déterminer les tournées optimales pour une flotte de véhicules afin de servir un ensemble donné de clients. Dans les problèmes classiques de transport, chaque client est normalement servi à partir d’un seul nœud (ou arc). Pour cela, on définit toujours un ensemble donné de nœuds (ou arcs) obligatoires à visiter ou traverser, et on recherche la solution à partir de cet ensemble de nœuds (ou arcs). Mais dans plusieurs applications réelles où un client peut être servi à partir de plus d’un nœud, (ou arc), les problèmes généralisés qui en résultent sont plus complexes. Le but principal de cette thèse est d’étudier trois problèmes généralisés de tournées de véhicules. Le premier problème de la tournée sur arcs suffisamment proche (CEARP), comporte une application réelle intéressante en routage pour le relevé des compteurs à distance ; les deux autres problèmes, problème de tournées couvrantes multi-véhicules (mCTP) et problème généralisé de tournées sur nœuds (GVRP), permettent de modéliser des problèmes de conception des réseaux de transport à deux niveaux. Pour résoudre ces problèmes, nous proposons une approche exacte ainsi que des métaheuristiques. Pour développer la méthode exacte, nous formulons chaque problème comme un programme mathématique, puis nous construisons des algorithmes de type branchement et coupes. Les métaheuristiques sont basées sur le ELS (ou Evolutionary Local Search) et sur le GRASP (ou Greedy Randomized Adaptive Search Procedure). De nombreuses expérimentations montrent la performance de nos méthodes. / The Routing Problem is one of the most popular and challenging combinatorial optimization problems. It involves finding the optimal set of routes for fleet of vehicles in order to serve a given set of customers. In the classic transportation problems, each customer is normally served by only one node (or arc). Therefore, there is always a given set of required nodes (or arcs) that have to be visited or traversed, and we just need to find the solution from this set of nodes (or arcs). But in many real applications where a customer can be served by from more than one node (or arc), the generalized resulting problems are more complex. The primary goal of this thesis is to study three generalized routing problems. The first one, the Close-Enough Arc Routing Problem(CEARP), has an interesting real-life application to routing for meter reading while the others two, the multi-vehicle Covering Tour Problem (mCTP) and the Generalized Vehicle Routing Problem(GVRP), can model problems concerned with the design of bilevel transportation networks. The problems are solved by exact methods as well as metaheuristics. To develop exact methods, we formulate each problem as a mathematical program, and then develop branch-and-cut algorithms. The metaheuristics are based on the evolutionary local search (ELS) method et on the greedy randomized adaptive search procedure (GRASP) method. The extensive computational experiments show the performance of our methods.

This thesis presents two new routing problems, both with objective functions focused on relative positioning of teams during the routing horizon. The relative positioning results in temporal and spatial dependencies among routes and is quantified with a nonlinear dispersion metric, designed to evaluate the instantaneous distances among teams over a time interval. This metric allows the design of objective functions to approximate teams during routes execution, when minimized, or disperse them, when maximized. Both approximation and dispersion are important routing characteristics in some practical applications, and two new optimization problems are proposed with these opposite objectives. The first one is a variation of the Multiple Traveling Salesman Problem, and its goal is to find a set of tours where the salesmen travel close to each other, minimizing dispersion. A Local Search Genetic Algorithm is proposed to solve the problem. It includes specialized genetic operators and neighborhoods. A new set of benchmark instances is proposed, adapted for the new problem from literature instances. Computational results show that the proposed approach provides solutions with the desired characteristics of minimal dispersion. The second problem is a bi-objective arc routing problem in which routes must be constructed in order to maximize collected profit and dispersion of teams. The maximization of the dispersion metric fosters the scattering of the teams during routing procedure. Usually, profit and dispersion objectives are conflicting, and by using a bi-objective approach the decision maker is able to choose a trade-off between collecting profits and scattering teams. Two solution methods are proposed, a Multi-objective Genetic Algorithm and a Multi-objective Genetic Local Search Algorithm, both specialized in order to exploit the characteristics of the problem. It is demonstrated, by means of computational experiments on a new set of benchmark instances, that the proposed approach provides approximation sets with the desired characteristics. / Esta tese apresenta dois novos problemas de roteamento, ambos com funções objetivo voltadas para o posicionamento relativo das equipes durante o horizonte de roteamento. O posicionamento relativo resulta em uma dependência temporal e espacial entre rotas e é quantificado com uma métrica de dispersão não-linear, projetada para avaliar as distâncias instantâneas entre as equipes ao longo de um intervalo de tempo. Esta métrica permite a concepção de funções objetivo para aproximar as equipes durante a execução das rotas, quando minimizada, ou para dispersá-las, quando maximizada. Tanto a aproximação quanto a dispersão são características importantes de roteamento em algumas aplicações práticas, e dois novos problemas de otimização são propostos com esses objetivos opostos. O primeiro é uma variação do Problema de Múltiplos Caixeiros Viajantes, e seu objetivo é encontrar um conjunto de rotas em que os caixeiros viajam próximos uns dos outros, minimizando a dispersão. Um Algoritmo Genético com Busca Local é proposto para resolver o problema. Ele inclui operadores genéticos e vizinhanças especializados. Um novo conjunto de instâncias é proposto, adaptado para o novo problema de instâncias da literatura. Resultados computacionais mostram que a abordagem proposta proporciona soluções com as características desejadas de dispersão mínima. O segundo problema é um problema de roteamento de arcos biobjetivo em que as rotas devem ser construídas de modo a maximizar o lucro recolhido e o distanciamento entre as equipes. A maximização da métrica promove a dispersão das equipes durante a execução das rotas. Normalmente, os objetivos de lucro e dispersão são conflitantes, e com uma abordagem biobjetivo o tomador de decisão é capaz de avaliar a troca entre a coleta de lucros e a dispersão de equipes. Dois métodos de solução são propostos, um Algoritmo Genético Multiobjetivo e um Algoritmo Genético Multiobjetivo com Busca Local, ambos especializados para explorar as características do problema. É demonstrado, por meio de experimentos computacionais sobre um novo conjunto de instâncias, que a abordagem proposta fornece conjuntos de aproximação com as características desejadas.