Column Generation for the Container Relocation Problem

Container terminals offer transfer facilities to move containers from vessels to trucks, trains and barges and vice versa. Within the terminal the container yard serves as a temporary buffer where incoming containers are piled up in stacks. Only the topmost container of each stack can be accessed. If another container has to be retrieved, containers stored above it must be relocated first. Containers need to be transported to a ship or to trucks in a predefined sequence as fast as possible. Generally, this sequence does not match the stacking order within the yard. Therefore, a sequence of retrieval and relocation movements has to be determined that retrieves containers from the bay in the prescribed order with a minimum number of relocations. This problem is known as the container relocation problem. We apply an exact and a heuristic column generation approach to this problem. First results are very promising since both approaches provide very tight lower bounds on the minimum number of relocations

Combinaison d'un système de rendez-vous avec le problème d'affectation de ressources dans un terminal à conteneurs

The connection of a container terminal to its hinterland is a key area for competition. Therefore, more and more attention is paid to the service quality of inland transport modes such as trucks, trains and barges. An effcient allocation of internal material handling resources and the use of new strategies, such as truck appointment systems, can reduce the time vehicles spend at the terminal. We propose a mixed integer linear programming model, based on a network flow representation of the terminal, to determine the number of appointments to accept per time slot and an allocation of internal resources minimizing service times of trains and barges simultaneously. By comparing container terminals with and without appointment systems, we show that a truck appointment system is beneficial for trucks as well as for trains and barges

Branch and price approach for the container relocation problem

Container terminals offer transfer facilities to move containers from vessels to trucks, trains and barges and vice versa. Incoming containers are not immediately loaded on an outgoing vehicle, but stored in the yard for up to several days. The yard is divided into blocks with several bays consisting of stacks and tiers. Figure 1 illustrates these terms. Terminals stack containers to use their scare land efficiently. Only the topmost container of each stack can be accessed directly. If another container has to be retrieved, containers above have to be relocated. These unproductive moves cannot be avoided completely as little information about future retrievals is known when a container is stored. But, poor yard management increases the number of relocations and the time needed to retrieve containers. Thereby, it decreases the overall productivity of the terminal. The container (or block) relocation problem consists in minimizing the number of relocations during the retrieval process. The container relocation problem is shown to be NP-hard. We present a branch and price procedure to solve the problem exactly

Localisation de plateformes logistiques en milieu urbain

Depuis une dizaine d'années, la logistique urbaine suscite l'intérêt de bon nombre de chercheurs de communauté et nationalité variées. L'objet du travail présenté ici porte sur la localisation de plateformes logistiques dans des zones urbaines denses

The Multi Trip Vehicle Routing Problem with Time Windows and Release Dates

The Multi-Trip Vehicle Routing Problem with Time Windows and Release Dates is a variant of the Multi-Trip Vehicle Routing Problem where a time windows is associated with each customer and a release date is associated with each merchandise to be delivered at a certain client. The release date represents the moment the merchandise becomes available at the depot for final delivery. The problem is relevant in city logistics context, where delivery systems based on city distribution centers (CDC) are studied. Trucks arrive at the CDC during the whole working day to deliver goods that are transferred to eco-friendly vehicles in charge of accomplish final deliveries to customers. We propose a population-based algorithm for the problem based on giant tour representation of the chromosomes as well as a split procedure to obtain solutions from individuals

A Metaheuristic Method for the Multi Trip Vehicle Routing Problem

National audienceIn recent years the number of passengers and freight vehicles increased in urban areas causing traffic congestion and increasing air and noise pollution. The need of an efficient distribution system that takes into account distribution cost, but at the same time considers environmental aspects aims the concept of city logistics. Vehicles could have limited capacity, due to laws restriction imposed and the narrowness of streets that characterize historical parts of downtowns. Then, it seems normal to allow vehicles accomplish several trips during the working day. MTVRP arises in this context. A MA is proposed to face the problem

A modeling approach for locating logistics platforms for fast parcels delivery in urban areas

International audienceThis study aims at defining a framework for optimizing, in a sustainable way (i.e. economical, eco-friendly and societal), the location of logistics platforms in urban areas. A first case study for our work is the city of Marseilles (France) which already has a logistics platform right in its centre (ARENC: 41362 m2 of warehouses and offices). In this abstract, we first provide a precise description of the problem we intend to solve. We then propose a mathematical model for representing it. Preliminary experimentations, based on the city of Marseilles, are then described; figures and preliminary results which are proposed for this first case study are obtained thanks to a decision-making software we have implemented. Conclusions and future works are finally drawn

Plates-formes en centre ville pour la Logistique Urbaine: étude sur la ville de Marseille

International audienceCette étude, conduite dans le cadre du projet PLUME, se propose d'évaluer l'intérêt de la mise en œuvre de systèmes de distribution urbaine à partir de Zones Logistiques Urbaines. Nous visons à définir d'un point de vue organisationnel et fonctionnel les atouts économiques, environnementaux et sociétaux de ces systèmes; le but étant de fournir un cadre méthodologique pour guider leur mise en place. Un premier terrain d'analyse pour notre étude sera la ville de Marseille qui possède la particularité de disposer d'une ZLU en cœur de centre-ville avec la plate-forme logistique d'ARENC (41362 m2 d'entrepôts et de bureaux). Dans cet article, nous proposons de définir plus précisément notre problématique avant de donner un bref état de l'art des problèmes classiques de la Recherche Opérationnelle se rattachant à notre étude (Facility Location Problem, Network Design Problem et Green Logistics). Nous établissons enfin une liste d'éléments que nous chercherons à prendre en compte dans un modèle général

The City Logistics Facility Location Problem

National audienceThe aim of this work is to propose a new model that we call the City Logistics Facility Location Problem (CLFLP). Our purpose when introducing the CLFLP, is to capture essential aspects of distribution in cities, while maintaining a reasonable level of genericity and simplicity in the defintion of the problem. Practically, this model was adapted to the case of the city of Marseilles (France) and inserted into a Decision Support System. With a more academic point of view, the model could serve as a cornerstone for the development of new models and methods for strategic issues in city logistics

A relax-and-repair heuristic for the Swap-Body Vehicle Routing Problem

International audienceIn this paper we address the Swap-Body Vehicle Routing Problem, a variant of the Truck and Trailer Routing Problem. It was introduced in the VeRoLog Challenge 2014. We develop a solution approach that we coin Relax-and-Repair. It consists in solving a relaxed version of the SB-VRP and deriving a feasible solution by repairing the relaxed one. We embed this approach within a population-based heuristic. During computation we store all feasible routes in order to derive better solutions by solving a set-partitioning problem. In order to take advantages of nowadays multi-core machines, our algorithm is designed as a collaborative parallel population-based heuristic. Experimental results show that our relax-and-repair algorithm is very competitive and point the impact of each phase on the quality of the obtained solutions. The advantage of our approach is that it can be adapted to solve complex industrial routing problems