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.

Orientador: Prof. Dr. Cláudio Nogueira de Meneses / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Ciência da Computação, 2016. / Beyond a complex real world system composed by a set of sophisticated machines and qualied human resources distributed around manufacturing environment, the Auto In- dustry needs a little more to allow their products to reach the nal costumers. Loading vehicles like cars, trucks and vans into auto-carriers and designing routes to delivery sub- sets of vehicles to auto dealers according to their orders are relevant tasks in automotive value chain performed by transportation companies. Given the set of complex constraints related to diferent vehicle models (with diferent dimensions) to be feasibly loaded into dierent auto-carrier models plus the auto-carrier eet routing task, transportation com- panies must explore strong computational alternatives to address this optimization prob- lem. In fact, we explore in this dissertation a real world complex problem composed by two sub-problems, both belonging to NP-hard class: routing and loading. After formally dening the tackled problem, we adopt, in this dissertation, a previously studied procedure based on enumeration techniques for loading task and we propose an alternative approach employing Asynchronous Teams concept, which combines local search algorithms in order to cooperate to each other to try to resolve the routing sub-problem. Setting the results provided by our implementation of Iterated Local Search (ILS) approach (already proposed in literature for solving the routing sub-problem) as benchmark, we propose computational experiments considering real-world instances, to compare performance of ILS to ve vari- ants of our Asynchronous Teams implementations. Final results evidence the power of this proposed alternative approach for founding quality solutions and its exibility to easily assume diferent configurations.

Made available in DSpace on 2016-06-02T19:52:00Z (GMT). No. of bitstreams: 1 DissRH.pdf: 983555 bytes, checksum: 2f6efc30e82bc4d5f60bb2893dd0bb3f (MD5) Previous issue date: 2004-12-16 / This research consists of the development of algorithms to solve the Periodic Vehicle Routing Problem (PVRP), wich has not received a great deal of attention in the O.R. literature. The objective of the PVRP is to elaborate a set of routes to attend to customers demand along a planning horizon. Each customer roquests that the visits occur in a combination predefined of days. Two heuristics were developed for the PVRP. In the first heuristic, three types of initial solution construction are used to attribute the customers to days. After that, visiting day combinations are changed in order to improvr the solution. The search process is controlled by an adaptative tabu heuristic from the literature which determines intensification and diversification actions, applied for each day in the period. The second heuristic incorporates a similar approach for the period as a whole. Computacional results show that this approach leads to good solution. / Esta pesquisa consiste no desenvolvimento de algoritmos para resolver o Problema de Roteamento de Veículos Periódico (PRPV), o qual tem sido pouco abordado na literatura de Pesquisa Operacional. O objetivo do PRVP é elaborar um conjunto de rotas para atender à demanda de cliente ao longo de um horizonte de planejamento. Cada cliente requer que as visitas aconteçam em uma combinação predefinida de dias. Foram desenvolvidas duas heurísticas para o PRPV, chamadas de VERSÃO 1 e VERSÃO 2. Na VERSÃO 1 são utilizados três tipos de construções iniciais para atribuir os clientes aos dias. Em seguida, são realizadas mudanças de combinações de dias de visitas na tentativa de melhorar a solução. O processo de busca por soluções é controlado por heurísitca tabu adaptativa da literatura que determina as ações de intensificação e diversificação, aplicado a cada dia do período. A VERSÃO 2 incorpora uma abordagem similar para o período como um todo. Resultados computacionais indicam que esta abordagem leva a soluções de boa qualidade.

A Roteirização de Veículos desempenha papel fundamental nos processos modernos de distribuição de produtos e realização de serviços. A atual disseminação de recursos de tecnologia de informação e comunicação, de forma confiável e economicamente acessível, permite trabalhar com informações em tempo real e melhoram os padrões de nível de serviço associados. O presente trabalho apresenta uma solução para roteirização de veículos cujas equipes de bordo realizam serviços que justificam seu deslocamento, uma vez que as demandas estão geograficamente dispersas. Tais demandas são, em parte, conhecidas antes do despacho (permitem programação antecipada) dos veículos e suas equipes; outra parte surge durante a jornada de trabalho. Como exemplos podem-se citar os casos de serviços de montagem e manutenção de instalações, equipamentos, engenharia e inspeção de tráfego, policiamento etc. Trata-se da aplicação da roteirização parcialmente dinâmica, conforme Larsen (2000), cujas bases foram definidas por Psaraftis (1988,1995), Bertsimas et al (1993) no problema DTRP (Dynamic Travelling Repairman Problem). A função objetivo apresenta uma combinação de minimização dos custos de deslocamento, para os pedidos de serviços conhecidos antes da saída dos veículos e de minimização do tempo de resposta (chegada no local do cliente ou da ocorrência) para os casos de pedidos imediatos ou emergenciais. A solução do problema envolve um modelo computacional de testes e avaliação, heurística de Clarke e Wright (1964) para formação das rotas estáticas, no Método Húngaro (Kuhn, 1955) para designar o veículo que resulta no menor tempo de resposta no atendimento a um pedido emergencial e a heurística de Clarke e Wright modificada na otimização do restante dos pedidos quando o veículo voltar a sua rota original. O modelo computacional foi testado em uma empresa de manutenção de elevadores na cidade de São Paulo, Brasil, onde demonstrou resultados comparativamente melhores em relação ao sistema de roteirização utilizado atualmente pela empresa. / The Vehicle Routing Problem plays a critical role on modern processes related to physical distribution of goods and services. The present expansion of information and communication technology in a reliable, economic and accessible way allows real time information and requires the utilization of appropriate tools for real time decisions resulting in significant improvements in quality and service level related to dynamic vehicle routing. A dynamic routing problem is presented, in which vehicles serve geographic dispersed service demands that justify their movement in a fixed area. Such service demands are partially known before vehicles dispatching (allowing prior programming) whilst others are known during the work journey. As examples, one can mention cases concerning installation and maintenance of utilities, equipment, engineering and surveillance services that refer to applications of Partially Dynamic Routing according to Larsen (2000), the groundings of which were defined by Psaraftis (1988,1995), Bertsimas et al (1993) in the Dynamic Travelling Repairman Problem (DTRP). The objective function is a combination of the minimization of movement costs to serve the prior demands and the minimization of time to reach (time to response) Dynamic-or-emergency-demand sites. The proposed solution involves a computational model for testing and evaluating a set of heuristics and methods comprising the Clarke and Wright (1964) Heuristic to compose the static routes, the Hungarian Method (Kuhn, 1955) to assign vehicles to the dynamic demands that produces the lowest response time and, finally, a Clarke and Wright Modified Heuristic used to optimize the remainder of the route when each diverted vehicle returns to its static route. The Computational Model was applied to a lift maintenance company located in the city of São Paulo (Brazil) demonstrating better results as compared to the present routing system.

A concern of logistics management is the correct and efficient use of the available fleet. The central focus of fleet management is determining the routes that will be used in customer service and the efficient allocation of available resources (vehicles). The correct fleet management can generate a competitive advantage. There is a problem in the Operations Research dedicated to working this type of situation, the Vehicle Routing Problem (VRP). The VRP tries to generate the most economical route to efficient use of the available fleet. The case study discussed in this work was a particular situation VRP where there is a heterogeneous fleet and where the collections and deliveries of passengers are carried at separate times. To solve this problem we designed a Genetic Algorithm. Additionally, three different crossover operators were tested in the search for better results. At the end of the study, the Genetic Algorithm was capable of solving the problem in a short time and finding the most economical way to generate routes, using efficiently the fleet and fulfilling all requests. / Uma das preocupaÃÃes da gestÃo logÃstica à a correta e eficiente utilizaÃÃo da frota disponÃvel. O foco central da gestÃo da frota està em determinar as rotas que serÃo utilizadas no atendimento aos clientes e a alocaÃÃo eficiente dos recursos (veÃculos) disponÃveis. A gestÃo correta da frota pode gerar um diferencial competitivo. Existe na Pesquisa Operacional um problema dedicado a trabalhar este tipo de situaÃÃo, denominado Problema de Roteamento de VeÃculos (PRV). O PRV procura gerar a rota mais econÃmica com utilizaÃÃo eficiente da frota disponÃvel. No estudo de caso, realizado neste trabalho, foi abordada uma situaÃÃo particular do PRV onde hà uma frota heterogÃnea e as coletas e entregas de passageiros sÃo realizadas em momentos separados. Para a resoluÃÃo deste problema foi desenvolvido e implementado um Algoritmo GenÃtico (AG). Adicionalmente, trÃs operadores de cruzamento diferentes foram testados na busca dos melhores resultados encontrados pelo AG. Ao final, o Algoritmo GenÃtico conseguiu se mostrar capaz de resolver o problema em tempo hÃbil e de maneira a gerar rotas mais econÃmicas, utilizando eficientemente a frota e atendendo todas as solicitaÃÃes.

[pt] A busca pelo desenvolvimento sustentável tem como importante fator diferencial as fontes de energia renováveis. O biodiesel desponta como uma das alternativas mais relevantes, mas suas formas de obtenção no Rio de Janeiro não foram suficientemente investigadas. Este trabalho identifica a oportunidade da produção de biodiesel a partir de óleos residuais de fritura neste cenário, enfatizando os custos de transporte do óleo desde os principais produtores comerciais até a obtenção do biocombustível. O objetivo é avaliar os custos de forma a verificar a viabilidade do emprego desta alternativa. Para tanto, foram estudadas as diversas ferramentas de resolução do Problema de Roteamento de Veículos e foi proposto um algoritmo que visa à otimização dos custos. A formulação matemática utilizada baseia-se numa extensão de algoritmos clássicos, como o apresentado por Arenales et al. (2007), e nas equações desenvolvidas em Kallehauge (2006). Os resultados do modelo de roteamento, atrelados aos custos de produção, impostos e insumos, foram comparados com informações sobre a comercialização do biodiesel, comprovando sua viabilidade econômica. A consolidação dos dados obtidos aponta a produção de biodiesel a partir de óleo residual de fritura como viável, com custos logísticos equivalentes a R/tmp/aaaUFg8ya,19 por litro e custo final de R,22 por litro. / [en] The search for a sustainable development has in renewable energy sources an important differential factor. Biodiesel is one of the most important alternatives, but its obtainment forms in Rio de Janeiro have not been investigated enough. This work identifies the opportunity of biodiesel production from waste cooking oil in this scenery, emphasizing oil`s transport costs until factories, where it is possible to obtain biodiesel in its final form. The objective is to evaluate costs in order to verify viability of this alternative source of energy. Hence, this research analysed several tools for solving Vehicle Routing Problem and it proposes an algorithm that results in cost optimization. The adapted mathematic formulation is based in an extension of classic algorithms, like those presented by Arenales (2007), and in equations developed by Kallehauge (2006). The routing model results, linked to production, tributes and input costs, have been compared with information about biodiesel commercialization, verifying its economic viability. The data consolidation obtained indicates that the biodiesel production from waste cooking oil is viable, with logistic costs equal to R/tmp/aaaPLIh7a,19 per liter and final cost equal to R,22 per liter.

Cette thèse a pour but d’apporter des solutions méthodologiques pour la mutualisation des transports entre les fournisseurs et les plateformes de la grande distribution. Cette mutualisation permet en effet de réduire les coûts, les émissions de CO2, et d’augmenter la qualité de service. Elle est organisée autour d’un réseau de plateformes de cross-docking appelées Centres de Routage Collaboratifs, développé par la société 4S Network. Nos travaux consistent à modéliser et résoudre à l’aide de techniques de recherche opérationnelle plusieurs problèmes d’optimisation du transport dans le réseau mutualisé. Le verrou scientifique majeur est de résoudre conjointement un problème de plan de chargement (Service Network Design Problem) dans un réseau logistique national, et des problèmes de tournées de véhicules à une échelle régionale. Nous prenons en compte des contraintes additionnelles issues du monde industriel et les tarifs réellement pratiqués par les transporteurs, notamment des coûts non linéaires.Les problèmes d’optimisation résultants sont résolus au moyen de méthodes ditesmatheuristiques, c’est-à-dire combinant des approches exactes telles que la génération de colonnes et des approches (méta)heuristiques telles que la recherche tabou. Les algorithmes développés dans cette thèse ont donné lieu à unoutil logiciel aujourd’hui en exploitation chez 4S Network. / The main purpose of this PhD. thesis is to provide methodological solutions for a collaborative transport between suppliers and retail platforms. The outcomes of this collaboration are numerous:cost reduction, greenhouse gas emission reduction and higher quality of service. The network is structured around cross-docking platforms developed by the company 4S Network. We model and solve several optimization problems in this collaborative network, using operationsresearch techniques. The major scientific challenge is to simultaneously solve a Service Network Design Problem in a national logistics network and several Vehicle Routing Problems at regional level. We consider additional constraints and prevailing pricing arising from the carriers, in particular non-linear costs. The resulting optimization problems are solved by matheuristic methods, that combine exact approaches as column generation and (meta)heuristic approaches as tabu search. The algorithms developed in this thesis are the core functions of a software tool developed for 4S network.

Die Tourenbildung beschäftigt sich mit der Konstruktion kostengünstiger Transportrouten zur Belieferung von Verbrauchern. Sie ist eine der weitreichensten Erfolgsgeschichten des Operations Research. Das starke Interesse an diesen Problemen durch Industrie und Forschung liegt zum einen am wirtschaftlichen Potenzial der Tourenbildung und -optimierung, zum anderen macht ihr Reichtum an Struktur sie zu einem faszinierenden Forschungsgebiet. In der vorliegenden Arbeit soll ein Überblick über einige, u. a. auch neuere mathematische Modell- und Lösungsansätze gegeben werden. Auf Grund der hohen Anzahl der Veröffentlichungen auf diesem Gebiet wird nicht zwingend ein Anspruch auf die vollständige Darlegung aller möglichen Problemstellungen im Zusammenhang mit dem TSP sowie dem VRP und deren Lösungsansätze erhoben. An den gegebenen Stellen wird statt dessen auf weiterführende Literatur verwiesen.

Vehicle Routing Problem with Time Windows is a hard optimization problem. Even though it has numerous practical applications, the question of solving it efficiently has not been satisfyingly solved yet. This thesis studies the Vehicle Routing Problem with Time Windows and presents several new algorithms for solving it. There are two heuristics presented here, as well as several more complex algorithms which use those heuristics as their components. The efficiency of presented techniques is evaluated experimentally using a set of test samples. As a part of this thesis, I have also developed a desktop application which implements presented algorithms and provides a few additional features useful for solving routing prob-lems in practice. Among others, there is a generator of pseudo-random problem instances and several visualization methods.

The objective of the thesis is to analyze the company´s expenses associated with relocation of the distribution centre as well as to describe the components of expenses associated with transport between company and customers. An important part of the thesis is comparison of the individual delivery routes. The theoretical part provides a brief description of Vehicle Routing Problem and its modifications as well as the different options how to solve it. The expenses calculations of truck transport are approximated to the reader. The practical part shows the real problem of Nestlé. The decreasing of the expenses is shown on real data. The reason of decreasing is the relocation of the distribution centre. The model routes are compared with the actual ones using MPL. It also shows the potential cost reduction.