Este trabalho aborda um problema ainda não explorado na literatura denominado 3L-FSMVRPTW (three-dimensional loading fleet sizing and mix vehicle routing problem with time windows), que compreende resolver simultaneamente o roteamento e carregamento tridimensional de veículos considerando frota heterogênea e janela de tempo. Foi desenvolvido um algoritmo específico para resolver o problema, denominado 3DC. Neste algoritmo foram introduzidas algumas inovações, entre elas, um novo operador de busca local (k-IntensiveSwap) e uma nova heurística de carregamento de contêiner. O algoritmo foi comparado aos melhores resultados disponíveis na literatura para problemas particulares ao apresentado. Houve bom desempenho no caso do CLP (container loading problem), bom resultado na redução do tamanho de frota no caso do 3L-VRP (threedimensional loading vehicle routing problem) e desempenho superior ao problema mais complexo estudado, o 3L-VRPTW (three-dimensional loading vehicle routing problem with time windows). Finalmente, apresentou-se um conjunto de avaliação, instâncias e soluções, para o problema completo com frota heterogênea e janela de tempo. / This work presents a problem not treated yet on the literature referenced as 3L-FSMVRPTW (three-dimensional loading fleet sizing and mix vehicle routing problem with time windows), which deals simultaneously with vehicle routing and its three-dimensional loading considering heterogeneous fleet and time windows. The algorithm developed for the specific problem is called 3DC. This algorithm introduces a new local search operator called k-IntensiveSwap and a new container loading heuristic. The results are compared with the best-known results from literature for particular problems embeeded on the general problem presented. The quality of solution was good in comparison other methods for CLP (container loading problem), it has good results in terms of reduction fleet sizing in the case of 3L-VRP (three-dimensional loading vehicle routing problem) and as for 3L-VRPTW (threedimensional loading vehicle routing problem with time windows) the performance was very superior. Finally, it is presented a solution set as benchmark for future comparison with the general problem, with heterogeneous fleet.

As localizações dos terminais e as rotas de entrega que partem desses terminais são decisões importantes que surgem na concepção de redes de transporte de carga fracionada. Nesses casos, dois problemas independentes precisam ser tratados: o problema da localização de instalações (LAP) e o problema da roteirização dos veículos (VRP). Este trabalho apresenta um modelo matemático para resolver o LAP e o VRP de forma integrada, ou seja, para a resolução do problema de Localização/Roteirização (Location Routing Problem - LRP). De acordo com a literatura, a abordagem integrada do LRP fornece melhores resultados do que a solução do LAP e do VRP separadamente. O modelo foi testado e aplicado em um caso real de Many-to-Many com Multiplos elos LRP, respeitou as restrições e o nível de serviço exigido e propiciou melhoria nos resultados para a empresa de transporte no qual foi aplicado. Os resultados do modelo também foram melhores do que os resultados apresentados por um software líder de mercado. / In the Less Than Truck Load (LTL) operations both the location of facilities and the routing of vehicles are important decisions for the optimal design of the related logistics network. Two interdependent problems arise: the Location Allocation Problem (LAP) and the Vehicle Routing Problem (VRP). This paper presents a mathematical model to solve the LAP and the VRP simultaneously on an integrated way, such as the so-called Location-Routing Problem (LRP). According to the literature the LRP integrated approach provides better results than considering the LAP and the VRP separately. The model was tested and applied to a real case of Many-to-Many with Multi-Echelons LTL Location-Routing Problem respecting the constraints and the required service level standard and provided better results for the company in which it was tested. The model results also were better than the results presented by market-leading software.

Made available in DSpace on 2016-12-23T14:05:52Z (GMT). No. of bitstreams: 1 Rosemberg Silva Salles.pdf: 2088047 bytes, checksum: b650ba6ed0d06eb04f22760620fd4cc1 (MD5) Previous issue date: 2013-05-21 / This work aims to develop a procedure for collecting and physical distribution of employees by a fleet of chartered buses with the support of a geographic information system by applying the vehicle routing problem for possible optimization of routes. We begin with a review of the literature on chartered transport of employees, as well as the problems of vehicle routing and geographic information systems. Then we propose a routing procedure, which characterizes and defines the problem of collection and delivery of employees, in addition to defining the criteria for route ptimization. For this purpose, we use the software TransCAD where you do the modeling and the resolution of the problem. The procedure was applied to a case study in a large company in the Metropolitan Region of Vitória in Espírito Santo State, which provides transport their own to their employees. We generated four scenarios, analyzing the efficiency of the routes in terms of distances, travel times and operating costs. The results generated from the procedure allowed us to determine in what scenarios the routes are more efficient / Este estudo tem o objetivo de desenvolver um procedimento de coleta e distribuição física de empregados por uma frota de ônibus fretada com o apoio de um sistema de informações geográficas, aplicando o problema de roteirização de veículos para uma possível otimização das rotas. Inicialmente é feita uma revisão de literatura sobre o transporte fretado de empregados, bem como dos problemas de roteirização de veículos e dos sistemas de informações geográficas. Em seguida é proposto um procedimento de roteirização, onde se caracteriza e delimita o problema de coleta e distribuição de empregados, além de definir os critérios de otimização de rotas. Para tanto, utiliza-se o software TransCAD no qual é feita a modelagem e proposta de resolução do problema. O procedimento foi aplicado a um estudo de caso em uma empresa de grande porte na Região Metropolitana da Grande Vitória, no Estado do Espírito Santo, que oferece transporte próprio as seus empregados. Foram gerados quatro cenários, onde se analisa a eficiência das rotas em termos de distâncias, tempos de viagem e custos operacionais. Os resultados gerados a partir do procedimento permitiram determinar em que cenários as rotas se mostram mais eficientes

As localizações dos terminais e as rotas de entrega que partem desses terminais são decisões importantes que surgem na concepção de redes de transporte de carga fracionada. Nesses casos, dois problemas independentes precisam ser tratados: o problema da localização de instalações (LAP) e o problema da roteirização dos veículos (VRP). Este trabalho apresenta um modelo matemático para resolver o LAP e o VRP de forma integrada, ou seja, para a resolução do problema de Localização/Roteirização (Location Routing Problem - LRP). De acordo com a literatura, a abordagem integrada do LRP fornece melhores resultados do que a solução do LAP e do VRP separadamente. O modelo foi testado e aplicado em um caso real de Many-to-Many com Multiplos elos LRP, respeitou as restrições e o nível de serviço exigido e propiciou melhoria nos resultados para a empresa de transporte no qual foi aplicado. Os resultados do modelo também foram melhores do que os resultados apresentados por um software líder de mercado. / In the Less Than Truck Load (LTL) operations both the location of facilities and the routing of vehicles are important decisions for the optimal design of the related logistics network. Two interdependent problems arise: the Location Allocation Problem (LAP) and the Vehicle Routing Problem (VRP). This paper presents a mathematical model to solve the LAP and the VRP simultaneously on an integrated way, such as the so-called Location-Routing Problem (LRP). According to the literature the LRP integrated approach provides better results than considering the LAP and the VRP separately. The model was tested and applied to a real case of Many-to-Many with Multi-Echelons LTL Location-Routing Problem respecting the constraints and the required service level standard and provided better results for the company in which it was tested. The model results also were better than the results presented by market-leading software.

Fornecedores necessitam atender a demanda de seus clientes da forma mais adequada possível e mantendo a qualidade de seu serviço, porém em muitos casos essa demanda é desconhecida. Esse problema pode ser modelado como um problema de roteirização e estoque com demanda estocástica o qual inclui o controle de estoque, transporte do produto e decisões de agendamento da entrega. Existem vários trabalhos na literatura para resolver esse problema, porém nenhum deles lida com janela de tempo de atendimento, capacidade máxima de estoque tanto no cliente quanto no depósito e o nível de confiança de atendimento individualizado para cada cliente. O objetivo principal deste trabalho é propor um novo algoritmo baseado em otimização matemática para lidar com esse problema mais realista. Além disso, este trabalho tem como objetivo secundário melhorar o algoritmo de estado da arte baseado em otimização matemática, visando encontrar soluções com um menor tempo computacional e custo. Foram realizados experimentos com instâncias sintéticas com 15 até 50 clientes, as quais são geradas aleatoriamente, e com uma instância real, baseada na experiência profissional no mercado empresarial e em cenários reais de distribuição na cidade de São Paulo / Providers need to supply the demand of their clients as optimally as possible and maintaining the quality of their service, however in many cases this demand is unknown. This problem can be modeled as a inventory routing problem with stochastic demand, which includes inventory control, product transportation and delivery scheduling decisions. There are several papers in the literature to solve this problem, but none of them deals with service time window, maximum stock capacity for both the customer and the depot and individualized confidence level for each costumer. The main objective of this work is to propose a new algorithm based on mathematical optimization to deal with this more realistic problem. In addition, this work has as secondary objective to improve the state of the art algorithm based on mathematical optimization, aiming to find solutions with a lower computational time and cost. Experiments were performed with synthetic instances with 15 to 50 clients, which are randomly generated, and with a real instance, based on professional experience in the business market and in real distribution scenarios in the city of São Paulo

We define an order cutoff for a retailer as a time in the day such that orders sent to the depot before this point will be delivered by tomorrow, and orders submitted after will be delivered by the day after tomorrow. The later a retailer’s cutoff, the sooner it receives its orders which helps it to maintain ideal inventory levels. Generally, not all retailers in a supply chain can have the latest cutoff since transportation takes a significant amount of time. This thesis tries to assign optimal order cutoffs to retailers. We call this an order cutoff assignment problem and we solve it using three different mathematical programming approaches. The approaches are exhaustive route generation and selection, a series of mixed integer programs, and branch-and-price. 60 sample problems were solved and results showed that branch-and-price is often the most effective method.

We define an order cutoff for a retailer as a time in the day such that orders sent to the depot before this point will be delivered by tomorrow, and orders submitted after will be delivered by the day after tomorrow. The later a retailer’s cutoff, the sooner it receives its orders which helps it to maintain ideal inventory levels. Generally, not all retailers in a supply chain can have the latest cutoff since transportation takes a significant amount of time. This thesis tries to assign optimal order cutoffs to retailers. We call this an order cutoff assignment problem and we solve it using three different mathematical programming approaches. The approaches are exhaustive route generation and selection, a series of mixed integer programs, and branch-and-price. 60 sample problems were solved and results showed that branch-and-price is often the most effective method.

The emphasis on minimizing the logistics costs to decrease overall system costs has led the researchers to consider the interdependencies between the decisions of locating facilities and planning the routes from those facilities. The location-routing problems considering this issue are the subject of this thesis study. A two-level hierarchical distribution system is considered in which goods are delivered from the sources (plants) to the facilities (depots) and then from the facilities to the customers. The facilities are uncapacitated and operate within the shift times defined. The goods are to be delivered to the customers within their time windows by the vehicles that are capacitated. Both a mathematical model and a genetic algorithm based heuristic solution approach are proposed for this problem. We discuss the problem specific issues integrated with the general framework of the genetic algorithm applications. The computational studies are realized on a number of test problems. The results indicate that the genetic algorithm based heuristic gives satisfactory results compared with a sequential solution methodology.

This study deals with a municipal solid waste management system in which the strategic and tactical decisions are addressed simultaneously. In the system, the number and locations of the transfer facilities which serve to the particular solid waste pick-up points and the landfill are determined. Additionally, routing plans are constructed for the vehicles which collect the solid waste from the pick-up points by regarding the load capacity of the vehicles and shift time restrictions. We formulate this reverse logistics system as a location-routing problem with two facility layers. Mathematical models of the problem are presented, and an iterative capacitated-k-medoids clustering-based heuristic method is proposed for the solution of the problem. Also, a sequential clustering-based heuristic method is presented as a benchmark to the iterative method. Computational studies are performed for both methods on the problem instances including up to 1000 pick-up points, 5 alternative transfer facility sites, and 25 vehicles. The results obtained show that the iterative clustering-based method developed achieves considerable improvement over the sequential clustering-based method.

In this study, the capacitated vehicle routing problem with shift based time constraints is taken into consideration. The study stemmed from an application in a cross dock. The considered cross dock is assumed to feed directly the production lines of its customer. The customer has a just-in-time production system that requires producing only in necessary quantities at the necessary times. This necessitates the arrival of the parts/products collected from different suppliers at the customer at the beginning of each shift of production. The shift times constitute deadlines for the products to be collected from the suppliers and used in each shift. The collection problem then can be seen as the capacitated vehicle routing problem with shift based time constraints. The objective of the collection problem is to minimize the routing costs. For the accomplishment of this objective it is required to decide on products of which shift(s) should be taken from a supplier when a vehicle arrives at that supplier. For the solution of the problem a mathematical model is formulated. Since the dealt problem is NP-Hard, meta-heuristic solution approaches based on variable neighborhood search and simulated annealing are proposed. Computational experimentation is conducted on the test problems which are tailored from the capacitated vehicle routing instances from the literature.