Two-echelon vehicle routing problems which contain synchronization between vehicles can be deeply impacted by time uncertainty, because one vehicle's delay can propagate to other vehicles. In this paper, we evaluate the deterministic solution of such a problem based on simulated travel time scenarios. The information obtained by simulation is incorporated in the optimization procedure iteratively. Computational results show that the degree of synchronization in an instance is directly correlated with the potential improvements by reoptimization. We present findings on the number of travel time scenarios required to obtain a representative picture of the stochastic solutions. In addition, we demonstrate that time dependent travel times can be aggregated on a city-wide level and linearized as a function of free flow times without major loss of reliability.

O transporte de cargas desempenha um papel fundamental nos sistemas logísticos uma vez que possibilita o fluxo de produtos entre os elementos dos canais de distribuição, além de representar um elevado percentual de participação nos custos logísticos totais. Desse modo, a eficiência dos serviços de transporte depende diretamente de um adequado processo de planejamento em nível estratégico, tático e operacional. O transporte rodoviário, em particular, apresenta em nível operacional, problemas de elevada complexidade como a roteirização e o carregamento de veículos. Durante os últimos 50 anos estes problemas vêm sendo objeto de intensos estudos e desenvolvimentos, porém de forma separada, conduzindo a resultados difíceis de serem implementados nas situações práticas, devido à grande interdependência existente entre roteirização e carregamento de veículos. A resolução integrada destes dois problemas é recente na literatura, o que abre um campo bastante promissor para novos desenvolvimentos. Assim, esta tese tem como objetivo propor uma abordagem integrada de resolução para o problema de roteirização e carregamento de veículos onde, além das restrições de carregamento tridimensionais, as restrições de tempo de ciclo e distribuição de peso nos eixos são consideradas. Este modelo adota uma abordagem aproximativa que combina o uso de heurísticas para construção dos carregamentos com a metaheurística de Busca Tabu para melhoria dos roteiros de entrega. Para execução dos testes computacionais é proposto um conjunto de 12 instâncias que buscam simular situações práticas encontradas nas operações de entrega feitas por empresas de transporte e prestadores de serviços logísticos. A partir desse conjunto de instâncias são construídos cenários que avaliam o uso de diferentes tipos de veículos e os respectivos custos operacionais. Testes complementares realizados com um conjunto de 27 instâncias disponíveis na literatura, demonstram a capacidade do modelo proposto de atingir boas soluções em um tempo de processamento aceitável. / Freight transportation plays a fundamental role in logistics systems, once it enables the product flow between distribution channels elements, besides to represents a high percentage of participation on the total logistics costs. In this way, transport service efficiency depends directly of a suitable process of planning in strategic, tactical and operational level. The road transportation, in particular, shows in operational level high complexity problems as routing and loading of vehicles. During the last 50 years, these problems has been object of deep studies and developments, but in a separate manner, leading to results that are difficult to implement in practical situation due to the interdependence between routing and loading of vehicles. The integrated resolution of these two problems is recent in the literature, what opens a quite promising field for new developments. Thus, this thesis has as objective to propose an integrated resolution approach for the vehicle routing and loading where, besides the three-dimensional loading constraints, constraints, the time cicle and the distribution load over de axles are considered. This model adopts an approximated approach that combines the use of heuristics for loading construction with Tabu Search metaheuristics to improve the delivery routes. For computational tests execution is proposed a 12 instances set that tries to simulate practical situation found in delivery operations made by freight firms and thirty party logistics. From this instance set, it is built scenarios that evaluate the use of different vehicle types and the respectives operational costs. Complementary tests made with a 27 instances set available in literature show the capacity of proposed model to get good solutions in an acceptable computational time.

Este trabalho apresenta uma variação do problema de roteamento de veículos que permite o uso de veículos com múltiplos compartimentos. A necessidade de veículos com múltiplos compartimentos surge com frequência em aplicações práticas quando uma série de produtos, que possuem diferentes qualidades ou tipo, precisam ser transportados mas não podem ser misturados. Este problema é chamado na literatura de roteamento de veículos com múltiplos compartimentos (PRVMC). Nós propomos uma heurística busca tabu implementada em uma busca local iterada para resolver este problema. Experimentos foram feitos para avaliar a performance da busca tabu iterada e os resultados obtidos foram comparados com os resultados disponíveis na literatura. O algoritimo proposto é capaz de encontrar soluções melhores e em menos tempo de processamento que as heurísticas existentes. / We study a variant of the vehicle routing problem that allows vehicles with multiple compartments. The need for multiple compartments frequently arises in practical applications when there are several products of different quality or type, that must be kept or handled separately. The resulting problem is called the multi-compartment vehicle routing problem (MCVRP). We propose a tabu search heuristic and embed it into an iterated local search to solve the MCVRP. In several experiments we analyze the performance of the iterated tabu search and compare it with results from the literature. We find that it consistently produces solutions that are better than existing heuristic algorithms.

L’interconnexion croissante dans les systèmes de transports a conduit à la modélisation de nouvelles contraintes, dites contraintes de synchronisation, dans les problèmes de tournées de véhicules. Dans cette thèse, nous nous intéressons à deux cas dans lesquels ce type de problématiques apparaît. Dans un premier temps, nous proposons une méthode heuristique pour un problème à deux échelons rencontré pour la distribution de marchandises en ville. Dans un second temps, nous étudions l’intégration d’un cross-dock dans des tournées de collectes et livraisons. Une première contribution à ce sujet concerne le problème de tournées de véhicules avec cross-docking, et une seconde contribution intègre, en plus, des contraintes de ressources au cross-dock dans le problème de routage. Une méthode pour un problème de chargement 3D, étudié lors d’un stage doctoral en entreprise, est également présentée. / Transportation systems are more and more interconnected, this has lead to a new kind of constraints, called synchronization constraints, in vehicle routing problems. In this thesis, we study two cases in which this type of constraints arises. First, we propose a heuristic method for a two-echelon problem arising in City Logistics. Second, we study the integration of a cross-dockin pickup and delivery vehicle routing problems. To that end we propose a matheuristic for the vehicule routing problem with cross-docking, and we propose an extension of this problem that integrates specific resource synchonization constraints arising at the cross-dock. A method for a 3D loading problem is also presented.

Apesar de serem utilizados com sucesso em problemas de roteirização clássicos como o do caixeiro-viajante e o de roteirização de veículos com janelas de tempo, os algoritmos genéticos não apresentavam bons resultados nos problemas de roteirização de veículos sem janelas de tempo. Utilizando-se de uma tendência recente de hibridização de algoritmos genéticos, Prins (2004) elaborou um algoritmo para o problema de roteirização de veículos sem janelas de tempo, monoperíodo, e que obrigatoriamente atenda a todos os clientes cujos resultados, quando aplicado a instâncias de Christofides et al. (1979) e de Golden et al. (1998), são comparáveis aos melhores códigos elaborados com base na busca tabu. Diferentemente da maioria dos algoritmos genéticos apresentados para solução de problemas de roteirização de veículos, no método desenvolvido por Prins (2004) o cromossomo é composto apenas pelos pontos a serem atendidos, não contendo delimitadores de rotas. Estas são definidas a partir de um método de particionamento do cromossomo. Este trabalho implementa o algoritmo descrito por Prins (2004) e propõe a este melhorias em diversas de suas etapas, como inicialização, operação de crossover, operação de mutação, reinicialização e particionamento do cromossomo. As alterações implantadas são aplicadas às instâncias de Christofides et al. (1979) e comparadas com o algoritmo inicial em termos de qualidade de solução e tempo de processamento. Finalmente, é elaborado um algoritmo genético que contempla as alterações que obtiveram resultados positivos. / In the Vehicle Routing Problem (VRP) we seek for a set of minimum-cost vehicle routes for a fleet of identical vehicles, each starting and ending at a depot, such that each customer is visited exactly once and the total demand of any route does not exceed the vehicle capacity. Several families of heuristics have been proposed for the VRP. They can be broadly classified into two main classes: classical heuristics developed between 1960 and 1990, and, more recently, metaheuristics. Among them, tabu search plays an key role, being acknowledged by most authors as the most successful approach for the VRP. In the literature some successful implementations of metaheuristic Genetic Algorithm (GA) can be found for classic routing problems such as the traveling salesman and vehicle routing problems with time windows. However, until recently, the same did not apply for the VRP. In this thesis we develop a genetic algorithm without trip delimiters, and hybridized with a local search procedure, for the solving the VRP, which is based on the work of Prins (2004). At any time, a chromosome can be converted into an optimal VRP solution (subject to chromosome sequence) by means of a splitting procedure, in which the chromosome sequence, representing a giant tour, is partitioned into feasible routes in terms of vehicle capacities. Starting with the procedure originally proposed Prins (2004), we then introduce new improvements in terms of the different components of the GA, aiming to obtain improved solutions. These include how we determine the initial population, different partitioning approaches, alternative reproduction (crossover) processes, a granular tabu mechanism similar to the one proposed by Toth and Vigo (2003 and, finally, in changes in the reinitialization process, aiming to reestablish diversity. Computational experiments are presented, based on the 14 classical Christofides instances for the VRP. The results show that the proposed improved versions of the GA allow us to obtain better solutions when compared to the original approach by Prins (2004).

When a package is shipped, the customer often requires the delivery to be made within a particular time window or by a deadline. However, meeting such time requirements is difficult, and delivery companies may not always know ahead of time which customers will need a delivery. In this thesis, we present models and solution approaches for two stochastic last-mile delivery problems in which customers have delivery time constraints and customer presence is known in advance only according to a probability distribution. Our solutions can help reduce the operational costs of delivery while improving customer service. The first problem is the probabilistic traveling salesman problem with time windows (PTSPTW). In the PTSPTW, customers have both a time window and a probability of needing a delivery on any given day. The objective is to find a pre-planned route with an expected minimum cost. We present computational results that characterize the PTSPTW solutions. We provide insights for practitioners on when solving the PTSPTW is beneficial compared to solving the deterministic analogue of the problem. The second problem is the same-day delivery problem (SDDP). The SDDP is a dynamic and stochastic pick-up and delivery problem. In the SDDP, customers make delivery requests throughout the day and vehicles are dispatched from a warehouse or brick and mortar store to serve the requests. Associated with each request is a request deadline or time window. In order to make better-informed decisions, our solution approach incorporates information about future requests into routing decisions by using a sample scenario planning approach with a consensus function. We also introduce an analytical result that identifies when it is beneficial for vehicles to wait at the depot. We present a wide range of computational experiments that demonstrate the value of our approaches.

Data-driven decision making has become more popular in today’s businesses including logistics and vehicle routing. Leveraging historical data, companies can achieve goals such as customer satisfaction management, scalable and efficient operation, and higher overall revenue. In the management of customer satisfaction, logistics companies use consistent assignment of their drivers to customers over time. Creating this consistency takes time and depends on the history experienced between the company and the customer. While pursuing this goal, companies trade off the cost of capacity with consistency because demand is unknown on a daily basis. We propose concepts and methods that enable a parcel delivery company to balance the trade-off between cost and customer satisfaction. We use clustering methods that use cumulative historical service data to generate better consistency using the information entropy measure. Parcel delivery companies route many vehicles to serve customer requests on a daily basis. While clustering was important to the development of early routing algorithms, modern solution methods rely on metaheuristics, which are not easily deployable and often do not have open source code bases. We propose a two-stage, shape-based clustering approach that efficiently obtains a clustering of delivery request locations. Our solution technique is based on creating clusters that form certain shapes with respect to the depot. We obtain a routing solution by ordering all locations in every cluster separately. Our results are competitive with a state-of-the-art vehicle routing solver in terms of quality. Moreover, the results show that the algorithm is more scalable and is robust to problem parameters in terms of runtime. Fish trawling can be considered as a vehicle routing problem where the main objective is to maximize the amount of fish (revenue) facing uncertainty on catch. This uncertainty creates an embedded prediction problem before deciding where to harvest. Using previous catch data to train prediction models, we solve the routing problem a fish trawler faces using dynamically updated routing decisions allowing for spatiotemporal correlation in the random catch. We investigate the relationship between the quality of predictions and the quality of revenue generated as a result.

There is an increasing interest in sustainability and a growing debate about environmental policy measures aiming at the reduction of green house gas emissions across di erent economic sectors worldwide. The transportation sector is one major greenhouse gas emitter which is heavily regulated to reduce its dependance on oil. These regulations along with the growing customer awareness about global warming has led vehicle manufacturers to seek di erent technologies to improve vehicle e ciencies and reduce the green house gases emissions while at the same time meeting customer's expectation of mobility and exibility. Plug-in hybrid electric vehicles (PHEV) is one major promising solution for a smooth transition from oil dependent transportation sector to a clean electric based sector while not compromising the mobility and exibility of the drivers. In the medium term, plug-in hybrid electric vehicles (PHEV) can lead to signi cant reductions in transportation emissions. These vehicles are equipped with a larger battery than regular hybrid electric vehicles which can be recharged from the grid. For short trips, the PHEV can depend solely on the electric engine while for longer journeys the alternative fuel can assist the electric engine to achieve extended ranges. This is bene cial when the use pattern is mixed such that and short long distances needs to be covered. The plug-in hybrid electric vehicles are well-suited for logistics since they can avoid the possible disruption caused by charge depletion in case of all-electric vehicles with tight time schedules. The use of electricity and fuel gives rise to a new variant of the classical vehicle routing with time windows which we call the plug-in hybrid electric vehicle routing problem with time windows (PHEVRPTW). The objective of the PHEVRPTW is to minimize the routing costs of a eet of PHEVs by minimizing the time they run on gasoline while meeting the demand during the available time windows. As a result, the driver of the PHEV has two decisions to make at each node: (1) recharge the vehicle battery to achieve a longer range using electricity, or (2) continue to the next open time window with the option of using the alternative fuel. In this thesis, we present a mathematical formulation for the plug-in hybrid-electric vehicle routing problem with time windows. We solve this problem using a Lagrangian relaxation and we propose a new tabu search algorithm. We also present the rst results for the full adapted Solomon instances.

Expanderande städer resulterar i ökande behov av godstransporter och för att behålla en fungerande godsdistribution kan åtgärder behöva vidtas. Trafikstockning och försämrad stadsmiljö är negativa effekter som kan förknippas med en dåligt fungerande godsdistribution. Citylogistik handlar om att kontrollera och optimera godstransporter i urbana områden (city) så att negativa effekter minimeras. Olika typer av citylogistiska åtgärder och koncept har identifierats. Till dem hör till exempel samdistribution, reglering av godstransporter och avancerade IT-system. Inom ramen för projektet SAMLIC, som startades i Linköping 2004, genomfördes pilotförsöket PILOT med det övergripande syftet att utvärdera ekonomisk potential med samdistribution i Linköpings city. Under PILOT omsattes ett samdistributionskoncept i praktiken. En databas med information om godsdistributionen under försöket upprättades för senare analys. Syftet med detta examensarbete har varit att formulera matematiska modeller över godsdistributionen i ett medelstort city, som kan ge underlag för utvärdering av citylogistiska koncept och i synnerhet samdistributionskoncept. De matematiska modeller som tagits fram är optimeringsmodeller för ruttplanering och metoder för att lösa optimeringsmodellerna har implementerats. För att utvärdera modellerna och metoderna har en fallstudie av Linköpings city gjorts, med datamaterial från PILOT. Modellerna ger möjlighet till effektiva analyser och jämförelser av citylogistiska koncept. Fallstudien visar dessutom att optimering av godsdistributionen i city innebär god förbättringspotential vilket ger ytterligare motiv till att använda modeller som verktyg. / Urbanization and city expansion result in an increasing need of transportation of goods, and in order to maintain efficiency, measures are needed. The aim of city logistics is to minimize negative impacts associated with city center goods distribution, such as traffic congestion and negative impacts on the living environment. Several city logistic measures have previously been suggested, such as freight consolidation, governance and advanced IT systems. Within the SAMLIC project started in 2004, a demonstration project known as PILOT was carried out in central Linköping, wherein the concept of freight consolidation was applied in reality. The objective was to evaluate the economic potential of freight consolidation. The aim of this thesis was to formulate mathematical models of the distribution of goods in a medium sized Swedish city. The models are to be used in the evaluation of city logistic measures, focusing on freight consolidation. The distribution problem is modelled as a vehicle routing problem, and methods for solving the resulting optimization problems have been implemented. Using data from PILOT, the models have been applied on Linköping with the purpose of evaluating the methods, as well as investigating the potential of using models for planning the distribution of goods. Conclusions involve that analyses of, and comparisons between, city lo-gistic measures can be efficiently made using mathematical models. The case study also indicates that goods distribution can be improved through the use of optimization methods, which further motivates mathematical modelling.

In this study we discuss the Vehicle Routing Problem with multiple use of vehicles (VRPM). In this variant of the routing problem the vehicles may replenish at any time at the depot. We present a detailed review of existing literature and propose two mathematical models to solve the VRPM. For these two models and their several variants we provide computational results based on the test problems taken from the literature. We also discuss a case study in which we are simultaneously dealing with side constraints such as time windows, working hour limits, backhaul customers and a heterogeneous vehicle fleet.