Submitted by Nadir Basilio (nadirsb@uninove.br) on 2018-01-24T20:35:47Z No. of bitstreams: 1 Luigi Tavolaro Santini.pdf: 2357766 bytes, checksum: b70528f7db6bf88f1285744982eb4234 (MD5) / Made available in DSpace on 2018-01-24T20:35:47Z (GMT). No. of bitstreams: 1 Luigi Tavolaro Santini.pdf: 2357766 bytes, checksum: b70528f7db6bf88f1285744982eb4234 (MD5) Previous issue date: 2017-02-23 / The present work deals with the Capacitated Vehicle Routing Problem with Three-Dimensional Loading Constraints. This problem is difficult to solve exactly, still relatively little studied, but important in the logistics activities of movement, warehousing and transportation. This problem consists in minimizing the total traveled distance by a homogeneous fleet of vehicles that address the issue of deliveries of customer demands, in which these demands are composed of items that have three relevant spatial dimensions. The objective of the present work is to develop heuristic and metaheuristic algorithms to solve the problem in question. The algorithms are based on the Clarke & Wright and George & Robinson heuristics, and on the Iterated Local Search and Adaptive Large Neighborhood Search metaheuristics. In the proposed algorithm, the routing problem is firstly addressed by adapting the Clarke & Wright heuristic, creating routes that are used to verify the loading pattern, thus obtaining an initial solution. In the following, an extensive search in the solution neighborhood is applied with the Iterated Local Search metaheuristic. For the best results of this search, it is checked if the loading pattern is feasible using an adapted George & Robinson algorithm. If it is not feasible, the Adaptive Large Neighborhood Search metaheuristic is executed in an attempt to find a feasible solution to the loading problem. Instances from the literature are used to evaluate the efficiency of the developed methods. The results obtained for the routing problem individually were of paramount importance to ensure the effectiveness of the Iterated Local Search metaheuristic. For the loading problem individually, the tests were also satisfactory, allowing for several feasible loading patterns using the adapted George & Robinson algorithm and the Adaptive Large Neighborhood Search metaheuristic. The results obtained with the proposed algorithm for the integrated problem were also good, being very close to those in the literature and with computational time relatively lower. As perspectives for future research, it is intended to investigate more efficient ways of exploring the solution space of the integrated problem, as well as the use of other metaheuristics. / O presente trabalho trata do Problema de Roteamento de Veículos Capacitado com Restrições de Carregamento Tridimensional. Este é um problema de difícil solução exata, ainda relativamente pouco estudado, porém importante nas atividades logísticas de movimentação, armazenagem e transporte de produtos. Este problema consiste em minimizar a distância total percorrida por uma frota homogênea de veículos que supram a questão das entregas das demandas de clientes, em que tais demandas são compostas por itens que possuem três dimensões espaciais relevantes. O objetivo do presente trabalho consiste em desenvolver algoritmos heurísticos e meta-heurísticos para resolver o problema em questão. Os algoritmos são baseados nas heurísticas de Clarke & Wright e de George & Robinson, e nas meta-heurísticas Iterated Local Search e Adaptive Large Neighborhood Search. No algoritmo proposto, primeiro trata-se o problema de roteamento adaptando-se a heurística de Clarke & Wright, criando roteiros que são utilizados para a verificação do padrão de carregamento, tendo-se assim uma solução inicial. Em seguida, é aplicada uma busca extensiva na vizinhança com a meta-heurística Iterated Local Search. Para os melhores resultados desta busca, verifica-se se o padrão de carregamento é viável utilizando o algoritmo de George & Robinson adaptado. Nos casos em que não é viável, a meta-heurística Adaptive Large Neighborhood Search é executada na tentativa de se encontrar soluções viáveis para o problema de carregamento. Instâncias da literatura são utilizadas para avaliar a eficiência dos métodos desenvolvidos. Os resultados obtidos para o problema de roteamento separadamente foram de suma importância para assegurar a eficiência do meta-heurística Iterated Local Search. Para o problema de carregamento separadamente, os testes utilizando o algoritmo de George & Robinson adaptado e a meta-heurística Adaptive Large Neighborhood Search também foram satisfatórios, permitindo a obtenção de vários padrões de carregamento factíveis. Os resultados obtidos com o algoritmo proposto para o problema integrado também foram bons, sendo bastante próximos aos da literatura e com tempo computacional relativamente menor. Como perspectivas de pesquisas futuras, pretende-se estudar formas mais eficientes de se explorar o espaço de busca do problema integrado, bem como a utilização de outras meta-heurísticas.

Unternehmen der Transportbranche müssen gerade im operativen Tagesgeschäft bei der Tourenplanung und Transportdisposition Planungsprobleme lösen, die ein hohes Maß an Dynamik aufweisen. Speziell die Inputfaktoren der Tourenplanung sind größtenteils dynamisch und stochastisch. Aus Sicht des Autors kann die Qualität von Tourplanungsergebnissen durch die zeitnahe Berücksichtigung unvorhergesehener Ereignisse nachhaltig verbessert werden. Jedoch findet diese zunehmend erfolgskritische Funktionalität in der Literatur bisher nur unzureichend Beachtung, obwohl das Tourenplanungsproblem (Vehicle Routing Problem (VRP)) eines der wichtigsten und am meisten erforschten kombinatorischen Optimierungsprobleme ist. Verfahren für kapazitierte dynamische Tourenplanungsproblemstellungen sind in der Literatur kaum zu finden. Speziell im Bereich der Algorithmen, die eine große Lösungsgeschwindigkeit, eine leichte Verständlichkeit, eine aus praktischer Sicht akzeptable Lösungsgüte aufweisen und die Möglichkeit besitzen, die aktuellen Routenpläne der Fahrzeuge ausgehend von der momentanen geographischen Position real-time zu verändern, besteht Forschungsbedarf. Die Arbeit geht daher der Forschungsfrage nach, wie ein Verfahren für die dynamische Tourenplanung zu konstruieren ist, welches das kapazitierte dynamische Tourenplanungsproblem mit der Möglichkeit der Änderung des aktuellen Fahrzeugzuges unter Einhaltung sehr kurzer Rechenzeiten bei größtmöglicher Verständlichkeit löst. Durch die genannten Kriterien wird im Rahmen der Arbeit der Schwerpunkt auf die Modifikation von klassischen heuristischen Verfahren für die Lösung von dynamischen Tourenplanungsproblemen gelegt. Die Arbeit befasst sich sowohl mit dem Gesamtkonzept zur Disposition dynamischer Kunden als auch mit konkreten Modellen und Verfahren zur Lösung von Subproblemen innerhalb des Gesamtkonzeptes. Ferner erfolgt die Präsentation von umfangreichen Simulationsergebnissen, die auf der durchgeführten softwaretechnischen Implementierung der entwickelten Verfahren basieren. Die gute Anwendbarkeit der neuen Verfahren in der Praxis wird gezeigt. Zwecks der möglichst ganzheitlichen Betrachtung des Themengebietes erfolgt in der Arbeit zum einen sowohl die Erörterung von quantitativen als auch von qualitativen Aspekten der dynamischen Tourenplanung und zum anderen die Analyse von Schnittstellen zwischen der dynamischen Tourenplanung und eng damit verbundenen Bereichen wie Flottenmanagement oder Auftragseingang bzw. -disposition. Hierzu werden die Informationsflüsse zwischen den beteiligten Elementen im Rahmen des dynamischen Dispositionsprozesses aufgezeigt, telematische Komponenten zur Unterstützung des Informationsmanagements und der Informationsübertragung vorgestellt sowie die benötigten Inputdaten erläutert. Den Schwerpunkt der Arbeit stellt jedoch die Entwicklung von neuen quantitativen Methoden zur dynamischen Tourenplanung dar.

In this thesis we consider three challenging vehicle routing problems representing specific aspects of complex real-world problems: (i) the vehicle routing problem with unit demands, (ii) the preemptive stacker crane problem and (iii) a multi-period vehicle and technician routing problem. For the vehicle routing problem with units demands we continue research on the exponential multi-insertion neighborhood, investigate its properties and propose heuristic solution methods utilizing the neighborhood. For the preemptive stacker crane problem we study structural properties and provide bounds on the benefits of preemption and the benefits of so-called explicit drop nodes that are used exclusively to facilitate preemption. We propose construction heuristics that improve on the state-of-the-art in computational time and solution quality. The multi-period vehicle and technician routing problem is the subject of the VeRoLog Solver Challenge 2019. We develop a solution method that adapts to the limited computational budget and the given instance parameters. In summary, this thesis contributes to the structural analysis of the considered problems and proposes efficient heuristic solution methods that are effective even on large-scale instances and under tight restrictions of the computational budget. The methods combine global and local search approaches and take the available computational budget into account to realize an adaptive best-effort allocation of the resources.

A just-in-time supply pickup and delivery system (JSS) manages the logistic operations between a manufacturing plant and its suppliers by controlling the sequence, timing, and frequency of container pickups and parts deliveries, thereby coordinating internal conveyance, external conveyance, and the operation of cross-docking facilities. The system is important to just-in-time production lines that maintain small inventories. This research studies the logistics, supply chain, and production control of JSS. First, a new meta-heuristics approach (taboo search) is developed to solve a general frequency routing (GFR) problem that has been formulated in this dissertation with five types of constraints: flow, space, load, time, and heijunka. Also, a formulation for cross-dock routing (CDR) has been created and solved. Second, seven issues concerning the structure of JSS systems that employ the previously studied common frequency routing (CFR) problem (Chuah and Yingling, in press) are explored to understand their impacts on operational costs of the system. Finally, a discreteevent simulation model is developed to study JSS by looking at different types of variations in demand and studying their impacts on the stability of inventory levels in the system. The results show that GFR routes at high frequencies do not have common frequencies in the solution. There are some common frequencies at medium frequencies and none at low frequency, where effectively the problem is simply a vehicle routing problem (VRP) with time windows. CDR is an extension of VRP-type problems that can be solved quickly with meta-heuristic approaches. GFR, CDR, and CFR are practical routing strategies for JSS with taboo search or other types of meta-heuristics as solvers. By comparing GFR and CFR solutions to the same problems, it is shown that the impacts of CFR restrictions on cost are minimal and in many cases so small as to make simplier CFR routes desirable. The studies of JSS structural features on the operating costs of JSS systems under the assumption of CFR routes yielded interesting results. First, when suppliers are clustered, the routes become more efficient at mid-level, but not high or low, frequencies. Second, the cost increases with the number of suppliers. Third, negotiating broad time windows with suppliers is important for cost control in JSS systems. Fourth, an increase or decrease in production volumes uniformly shifts the solutions cost versus frequency curve. Fifth, increased vehicle capacity is important in reducing costs at low and medium frequencies but far less important at high frequencies. Lastly, load distributions among the suppliers are not important determinants of transportation costs as long as the average loads remain the same. Finally, a one-supplier, one-part-source simulation model shows that the systems inventory level tends to be sticky to the reordering level. JSS is very stable, but it requires reliable transportation to perform well. The impact to changes in kanban levels (e.g., as might occur between route planning intervals when production rates are adjusted) is relatively long term with dynamic after-effects on inventory levels that take a long time to dissapate. A gradual change in kanban levels may be introduced, prior to the changeover, to counter this effect.

Examensarbetet handlar om att minimera en total servicekostnad för företaget Chargestorm då de skall utföra service på sina laddningscentraler för elbilar. En ruttoptimering har gjorts som resulterar i ett antal rutter som är tänka att användas av en servicetekniker när denne åker runt och utför service på laddningscentralerna. En simulering har också gjorts för att påvisa de bästa tidsintervallen då olika typer av service kan ske, med målet att minimera den totala servicekostnaden.

This thesis deals with solving a real case from one specific part of Operations Research -- Discrete Models. The case can be classified as Vehicle Routing Problem (VRP) which is a subset of classical Travelling Salesman Problem (TSP). The VRP is modified TSP when requirements of customers and capacities of trucks play role. The data needed for calculations were taken from the real situation of Pivovar Svijany a.s. The problem can be defined as VRP with cars with different capacities and split delivery. Even though the mathematic model of the problem is known and described in the thesis, the size of the problem is too big to be optimized. Therefore heuristic was used to solve it. Because of the good computational results in the past the savings algorithm was chosen. Its model was set using Visual Basic for Applications (VBA). The thesis (among others) analyses the sensitivity of the output on the values of the factors that can be chosen by the analyst. At the end of the thesis the best found solution is presented and the initial and the new scheme of the circles are compared.

O presente trabalho trata da solução para o problema da elaboração de programações de transporte do sistema de distribuição de materiais da Força Aérea Brasileira (FAB). Essas programações de transporte consistem em definir os roteiros de entrega e coleta de materiais a serem realizadas simultaneamente em cada local de entrega/coleta a partir de um centro de distribuição, considerando-se a frota de veículos homogênea. Isto é característico de um Problema de Roteirização de Veículos com Coletas e Entregas Simultâneas (PRVCES). A gestão do sistema de distribuição física da FAB considera a complexidade desse sistema e os dados relativos às demandas de transporte de carga em cada um desses locais para elaborar as programações de transporte. Essas programações são elaboradas tendo em vista os limites de capacidade dos veículos, as características físicas das cargas e as prioridades de embarque. O gestor desse sistema possui boa visibilidade das demandas de transporte, porém, devido à grande quantidade de informações disponíveis e à elevada complexidade desse sistema, é impossível elaborarem-se manualmente programações de transporte que resultem em viagens de distribuição eficientes. O PRVCES foi resolvido por meio da meta-heurística Busca Dispersa (do inglês Scatter Search) integrada com a meta-heurística Descida em Vizinhança Variável (do inglês Variable Neighborhood Descent) utilizada como método de melhoria das soluções. Os resultados superaram ou se igualaram a alguns dos obtidos por outros autores para os mesmos problemas de teste com as mesmas restrições, o que demonstra que a Busca Dispersa implementada é competitiva para solucionar o PRVCES. Quanto à aplicação na FAB, os resultados mostraram que a utilização do método de solução desenvolvido resultará em programações de transporte elaboradas em curto tempo de processamento e que estas incidirão positivamente sobre a eficiência do sistema de distribuição de materiais da FAB. / This work deals with the solution to the problem of drawing up transport schedules in the material distribution system of the Brazilian Air Force (BAF). These transport schedules consist in defining the routes for material pickup and delivery to be accomplished simultaneously in each delivery/pickup location from a distribution center, considering a homogeneous fleet of vehicles. This is characteristic of a Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP). The management of the physical distribution of BAF considers the complexity of this system and the data regarding the cargo transport demands in each one of those locations to draw up transport schedules. These schedules are drawn up regarding the capacity limits of the vehicles, the physical characteristics of the cargoes and the shipping priorities. A good visibility of transport demands in each location is available to the manager of this system, but due to the great quantity of data to deal with and the high complexity of the physical distribution system of BAF, it is impossible to draw up transport schedules that result in efficient distribution trips. The VRPSDP was solved by means of the Scatter Search meta-heuristic integrated with the Variable Neighborhood Descent meta-heuristic as the solution improvement method. The results exceeded or equaled some of those obtained by other authors using the same test problems with the same restrictions, what indicates that the implemented Scatter Search is competitive to solve the VRPSDP. As for the application in the BAF, the results showed that using the solution method developed will result in schedules drawn up in short processing time and focused on the efficiency of the material distribution system of the BAF.

Esta dissertação trata do problema do agrupamento de cargas fracionadas na distribuição de cimento ensacado partindo de um depósito central. O problema consiste em definir quais entregas de cimento serão carregadas juntas em um determinado veículo, de modo a aproveitar ao máximo sua capacidade e ao mesmo tempo reduzir o custo com o frete pago aos transportadores que farão sua distribuição. Em especial, o método de resolução proposto pode ser dividido em três fases. Na primeira fase, as entregas pertencentes a um mesmo cliente são agrupadas prioritariamente. Na segunda fase, são agrupadas as entregas de clientes dentro de uma mesma cidade. Neste caso, uma simplificação necessária é considerar que todas as entregas de uma mesma cidade estão localizadas em um único ponto. Com isso, a distância entre os clientes se torna irrelevante e é proposto um método baseado em um algoritmo genético para resolução de problemas de bin-packing (BPP). Para a terceira fase, é considerado o agrupamento para pontos de entrega pertencentes a cidades diferentes, onde as distâncias rodoviárias são consideradas. Nesta etapa, é proposta uma variação do método anterior, incorporando ao modelo algumas heurísticas para resolução de problemas de roteirização de veículos, como o algoritmo de Clarke & Wright e o algoritmo do Vizinho Mais Próximo. / This thesis deals with the problem of merging less-than-truckload deliveries in bagged cement distribution from a central depot. The problem consists in defining which cement deliveries shall be loaded in each given vehicle, in order to maximize the vehicle full capacity as well as reduce carriers freights. Particularly, the solution method can be divided hierarchically in three stages. In the first stage, the deliveries from the same client are merged with priority. In the second stage, the deliveries from the same city are merged. In this case, a necessary assumption is to consider the deliveries from the same city as located in a single destination point. Consequently, the distances among deliveries can be assumed as irrelevant and a heuristic method is proposed, which relies on a genetic algorithm for the bin-packing problem (BPP). In the third stage, merging of different delivery points that are apart from each other is considered. For this step, a variation of the previous method is proposed, incorporating some heuristics to solve the vehicle routing problem, like the Clarke & Wrights savings algorithm and the Nearest Neighbor algorithm.

O presente trabalho aborda o sistema logístico usualmente denominado Vendor Managed Inventory (VMI), no qual o fornecedor controla e coordena as decisões de reabastecimento, sendo responsável por manter os estoques de seus clientes dentro de limites fixados de antemão. O modelo proposto incorpora ainda as decisões relativas à produção e manutenção de estoque por parte do fornecedor, além da utilização de frota heterogênea na distribuição, e busca a minimização dos custos totais do sistema. Quatro heurísticas de duas etapas são propostas para a resolução do problema abordado. A primeira etapa, comum a todas as heurísticas, baseia-se em uma heurística recentemente publicada na literatura e fornece uma solução inicial viável, utilizada como ponto de partida para a etapa de melhoria subsequente, na qual é utilizada a metaheurística busca tabu ou busca em vizinhança variável. As heurísticas propostas foram avaliadas em um conjunto de teste, sendo obtidos resultados melhores que os reportados na literatura em todas as instâncias testadas. Dentre as estratégias de solução avaliadas, destaca-se a heurística baseada em busca tabu com diversificação, que demonstrou ser superior às demais heurísticas propostas. Os resultados obtidos indicam ainda que, no caso da frota disponível ser heterogênea, é vantajosa a utilização de uma adaptação do procedimento de obtenção da solução inicial, como forma de privilegiar a utilização de veículos de maior eficiência. / This thesis deals with the logistic system usually called Vendor Managed Inventory (VMI). In this system the supplier controls and coordinates the supply decisions and is responsible for keeping the inventory of each of his clients within predetermined minimum and maximum levels. Heterogeneous fleet and production/stocking decisions at the supplier are considered as well, and the proposed model seeks to minimize the total system cost. Four two-stage heuristics are proposed for this problem. The first stage consists in an adaptation of a heuristic found in the bibliography, which provides an initial viable solution that will be improved in the second stage by means of the metaheuristics tabu search or variable neighborhood search. The proposed heuristics were tested on a set of benchmark instances with improvements found on the best known results in all of the tested instances. The obtained results indicate that the tabu search based heuristic with diversification strategy is clearly superior to the other proposed heuristics and that a better fleet utilization can be obtained in the case of heterogeneous fleet by a simple improvement in the first stage, that favors the selection of more efficient vehicles.

<div>Bike sharing system (BSS) is growing worldwide. Although bike sharing is viewed as a sustainable transportation mode, it still has environmental footprints from its operation (e.g., bike rebalancing using automobiles) and upstream impacts (e.g., bike and docking station manufacturing). Thus, evaluating the environmental impacts of a BSS from the life cycle perspective is vital to inform decision making for the system design and operation. In this study, we conducted a comparative life cycle assessment (LCA) of station-based and dock-less BSS in the U.S. The results show that dock-less BSS has a greenhouse gas (GHG) emissions factor of 118 g CO2-eq/bike-km in the base scenario, which is 82% higher than the station-based system. Bike rebalancing is the main source of GHG emissions, accounting for 36% and 73% of the station-based and dock-less systems, respectively. However, station-based BSS has 54% higher total normalized environmental impacts (TNEI), compared to dock-less BSS. The dock manufacturing dominants the TNEI (61%) of station-based BSS and the bike manufacturing contributes 52% of TNEI in dock-less BSS. BSS can also bring environmental benefits through substituting different transportation modes. Car trip replacement rate is the most important factor. The results suggest four key approaches to improve BSS environmental performance: 1) optimizing the bike distribution and rebalancing route or repositioning bikes using more sustainable approaches, 2) incentivizing more private car users to switch to using BSSs, 3) prolonging lifespans of docking infrastructure to significantly reduce the TNEI of station-based systems, and 4) increasing the bike utilization efficiency to improve the environmental performance of dock-less systems.</div><div>To improve the design of current BSS from the life cycle perspective, we first proposed a simulation framework to find the minimal fleet size and their layout of the system. Then we did a tradeoff analysis between bike fleet size and the rebalancing frequency to investigate the GHG emission if we rebalance once, twice and three times a day. The optimal BSS design and operation strategies that can minimize system GHG emission are identified for a dock-less system in Xiamen, China. The results show that at most 15% and 13% of the existing fleet size is required to serve all the trip demand on weekday and weekend, if we have a well-designed bike layout. The tradeoff analysis shows that the GHG emission may increase if we continue to reduce the fleet size through more frequent rebalancing work. Rebalancing once a day during the night is the optimal strategy in the base scenario. We also tested the impacts of other key factors (e.g., rebalancing vehicle fleet size, vehicle capacity and multiple depots) on results. The analysis results showed that using fewer vehicles with larger capacity could help to further reduce the GHG emission of rebalancing work. Besides, setting 3 depots in the system can help to reduce 30% of the GHG emission compared with 1-depot case, which benefits from the decrease of the commuting trip distance between depot and the serve region.</div>