A lexicographic minimax approach to the vehicle routing problem with route balancing

International audienceVehicle routing problems generally aim at designing routes that minimize transportation costs. However, in practical settings, many companies also pay attention at how the workload is distributed among its drivers. Accordingly, two main approaches for balancing the workload have been proposed in the literature. They are based on minimizing the duration of the longest route, or the difference between the longest and the shortest routes, respectively. Recently, it has been shown on several occasions that both approaches have some flaws. In order to model equity we investigate the lexicographic minimax approach, which is rooted in social choice theory. We define the leximax vehicle routing problem which considers the bi-objective optimization of transportation costs and of workload balancing. This problem is solved by a heuristic based on the multi-directional local search framework. It involves dedicated large neighborhood search operators. Several LNS operators are proposed and compared in experimentations

Optimization of customer orders routing in a collaborative distribution network

This paper presents a sequential approach for the assessment of a multi-layered distribution network from a cluster of collaborating suppliers to a large set of customers. The transportation network includes three segments: suppliers routes from suppliers to a consolidation and distribution center, full truckload routes toward regional distribution centers, and less-than-truckload distribution toward final customers. In every shipping date, the optimization problem consists of assigning customers to regional distribution centers and determining the routes of vehicles through the whole distribution network. This problem is first modeled as a Mixed Integer Linear Problem (MILP). Then, we propose to decompose it into three smaller MILPs that are solved sequentially in order to quickly provide a good approximate solution. The experiments on real data show that the decomposition method provides near optimal solutions within a few minutes while the original model would require hours of calculation

Location of distribution centers in a multi-period collaborative distribution network

International audienceThis paper presents a research study which aims at determining optimal locations of regional distribution centers in a collaborative distribution network. We consider a multi-layered distribution system between a cluster of suppliers from a given region and several thousands customers spread over the whole country. The optimization problem consists of finding the locations of intermediate logistics facilities called regional distribution centers and assigning customers to these facilities according to one year of historical data. The distribution system combines full truckload (FTL) routes and less-than-truckload (LTL) shipments. The use of several rates for transportation, as well as the high impact of seasonality implies that, for each shipping date, the number of FTL routes and the cost of LTL shipments should be precisely evaluated. This problem is modeled as a mixed integer linear problem and used as a decision aiding tool on a real case study related to the distribution of horticultural products in France

Feasibility algorithms for two pickup and delivery problems with transfers

International audienceThis presentation follows the PhD thesis of Renaud Masson [1] on the Pickup and Delivery Problem with Transfers (PDPT). The motivating application is a dial-a-ride problem in which a passenger may be transferred from the vehicle that picked him/her up to another vehicle at some predetermined location, called transfer point. Both the PDPT and the Dial-A-Ride Problem with Transfers (DARPT) were investigated. An adaptive large neighborhood search has been developed to solve the PDPT [2] and also adapted to the DARPT [3]. In both algorithms, multiple insertions of requests in routes are tested. E ciently evaluating their feasibility with respect to the temporal constraints of the problem is a key issue

Efficient handling of synchronization in three vehicle routing problems

International audienceThis paper presents a synthesis of contributions to the solving of three vehicle routing problemsinvolving synchronization constraints. These problems are: the Pickup and Delivery Problem withTransfers (PDPT), studied during the PhD of Renaud Masson, co-advised with Olivier Péton [4], theTwo-Echelon Multiple-Trip Vehicle Routing Problem with Satellite Synchronization (2E-MTVRPSS),studied by Philippe Grangier during his PhD, co-advised with Michel Gendreau and Louis-Martin Rousseau [2], and the Heterogeneous Full Truckload Pickup and Delivery Problem with TimeWindows and Resource Synchronization(HFTPDPTW-RS), under study by Axel Grimault in hisPhD and co-advised with Nathalie Bostel [3]. All these problems have been solved with an AdaptiveLarge Neighborhood Search (ALNS).A special focus is given to the temporal feasibility evaluation of an insertion which has beenproposed for the PDPT [5] and extended to the other problems. The concept of forward time slack[6] is extended to provide a constant time feasibility test of temporal constraints. Experimentsconfirm the solving time reduction provided by the implementation of this test in a meta-heuristic

An adaptive large neighborhood search for a full truckload routing problem in public works

International audienceThis paper presents a truck routing and scheduling problem faced by a public works company. Itconsists of optimizing the collection and delivery of materials between sites, using a heterogeneousfleet of vehicles. These flows of materials arise in levelling works and construction of roads networks.As the quantity of demands usually exceeds the capacity of a truck, several trucks are needed tofulfill them. As a result, demands are split into full truckloads. A set of trucks routes are needed toserve a set of demands sharing a set of resources, available at pickup or delivery sites, which can beloaders or asphalt finishers in our application cases. Thus, these routes need to be synchronized ateach resource. We propose an Adaptive Large Neighborhood Search (ALNS) to solve this problem.This approach is evaluated on real instances from a public work company in France

An adaptive large neighborhood search for a vehicle routing problem with cross-dock under dock resource constraints

International audienceIn this work, we study the impact of dock resource constraints on the cost of VRPCD solutions

Optimisation du transport mutualisé d'enfants en situation de handicap avec véhicules reconfigurables

National audienceEn 2010, le transport sanitaire est devenu l’une des dix priorités du plan de gestion des risques de l’Assurance maladie du fait de l’augmen-tation du coût de ces transports. Pour l’établissements médico-sociaux (EMS), ce coût représentent la deuxième dépense après celle du person-nel. Dans ce contexte, ce projet de recherche vise une amélioration globale de la prise en charge du transport quotidien des enfants en structuresde service médico-sociaux. En conséquence nous proposons la mutualisation du transport entre plusieurs EMS. Cette mutualisation du transportpermet de regrouper des tournées dans une certaine zone géographique. L’enjeu est d’améliorer la performance économique tout en maintenantdes objectifs économiques, sociaux et environnementaux. D’un point de vue scientifique ce problème est nommé le Dial-a-Ride Problem (DARP).Ce problème est démontre NP-Hard. Tout d’abord nous cherchons à intégrer au DARP avec véhicules adaptées la notion de reconfigurationpendant la tournée. Pour résoudre ce problème, nous utilisons la métaheuristique Large Neighborhood Search

A shared " passengers & goods " city logistics system

International audienceMany strategic planning models have been developed to help decision making in city logistics. Such models do not take into account, or very few, the flow of passengers because the considered unit does not have the same nature (a person is active and a good is passive). However, it seems fundamental to gather the goods and the passengers in one model when their respective transports interact with each other. In this context, we suggest assessing a shared passengers & goods city logistics system where the spare capacity of public transport is used to distribute goods toward the city core. We model the problem as a vehicle routing problem with transfers and give a mathematical formulation. Then we propose an Adaptive Large Neighborhood Search (ALNS) to solve it. This approach is evaluated on data sets generated following a field study in the city of La Rochelle in France

Optimization of a city logistics transportation system with mixed passengers and goods

International audienceIn this paper, we propose a mathematical model and an adaptive large neighborhood search to solve a two{tiered transportation problem arising in the distribution of goods in congested city cores. In the rst tier, goods are transported in city buses from a consolidation and distribution center to a set of bus stops. The main idea is to use the buses spare capacity to drive the goods in the city core. In the second tier, nal customers are distributed by a eet of near{zero emissions city freighters. This system requires transferring the goods from buses to city freighters at the bus stops. We model the corresponding optimization problem as a variant of the pickup and delivery problem with transfers and solve it with an adaptive large neighborhood search. To evaluate its results, lower bounds are calculated with a column generation approach. The algorithm is assessed on data sets derived from a eld study in the medium-sized city of La Rochelle in France