Ordonnancement de camions dans une plateforme logistique : complexité, méthodes de résolution et incertitudes

La problématique dite de crossdocking a été source de beaucoup d'attention ces dernières années dans la littérature. Un crossdock est une plateforme logistique favorisant, par une synchronisation efficace des camions entrants et sortants, une rotation rapide des produits, le volume de produits stockés devant être le plus faible possible. Le crossdocking soulève de nombreux problèmes logistiques, dont notamment celui de l'ordonnancement des camions entrants et sortants sur les quais de la plateforme. L'objectif classiquement considéré dans la littérature pour ce problème est la minimisation du makespan, critère très répandu en d'ordonnancement. Pour le crossdocking néanmoins, minimiser la date de départ du dernier camion ne garantie pas nécessairement une bonne synchronisation des camions et le makespan ne semble donc pas être l'objectif le plus pertinent. Pour répondre au besoin de synchronisation et favoriser les rotations rapides, notre travail propose alternativement de minimiser la somme des temps de séjour des palettes dans le stock. Nous étudions d'abord la version déterministe de ce problème d'ordonnancement. Sa complexité est détaillée selon différentes hypothèses pour identifier les éléments menant à sa NP-difficulté. Différentes méthodes de résolutions sont proposées. Une méthode classique de programmation linéaire en nombres entiers utilisant des variables de décision indexées par le temps. Une famille d'inégalités valides est également proposée et exploitée dans un algorithme avec ajout itératif de coupes. Des méthodes basées sur la programmation par contraintes sont enfin proposées. Une analyse comparative de ces différentes méthodes est proposée. Dans un deuxième temps, nous étudions une version non-déterministe de notre problème d'ordonnancement dans laquelle des incertitudes sur les dates d'arrivée des camions sont introduites sous la forme d'intervalles de temps équiprobables. Une méthode d'ordonnancement proactive-réactive utilisant le concept de groupes d'opérations permutables est proposée pour faire face aux incertitudes. Des groupes de camions permutables sont séquencés et affectés aux quais puis, durant l'exécution d'ordonnancement, en fonction de la réalisation des dates d'arrivée, un ordre est choisi dans chaque groupe à l'aide d'un algorithme réactif.Crossdocking has received a lot of attention in the literature in recent years. A crossdock is a logistic platform that promotes rapid product turnover through efficient synchronization of incoming and outgoing trucks, with the volume of products stored being kept as low as possible. Crossdocking raises many logistical problems, including the scheduling of incoming and outgoing trucks on the platform's docks. The classical objective considered in the literature for this problem is the minimization of the makespan, a very common criterion in scheduling. However, for crossdocking, minimizing the departure date of the last truck does not necessarily guarantee a good synchronization of the trucks and the makespan does not seem to be the most relevant objective. In order to meet the need for synchronization and to help fast rotations, our work proposes alternatively to minimize the sum of the pallets' sojourn times in the warehouse. We first study the deterministic version of this scheduling problem. Its complexity is detailed under different assumptions to identify the elements leading to its NP-hardness. Different solution methods are proposed. A classical integer linear programming method using time-indexed decision variables. A family of valid inequalities is also proposed and exploited in an algorithm with iterative addition of cuts. Finally, methods based on constraint programming are proposed. A comparative analysis of these different methods is proposed. In a second step, we study a non-deterministic version of our scheduling problem in which uncertainties on truck arrival dates are introduced in the form of equiprobable time intervals. A proactive-reactive scheduling method using the concept of permutable operation groups is proposed to cope with the uncertainties. Groups of permutable trucks are sequenced and assigned to the docks and then, during the scheduling run, based on the realization of arrival dates, an order is chosen in each group using a reactive algorithm

Unveiling Hidden Values of Optimization Models with Metaheuristic Approach

Considering that the decision making process for constrained optimization problem is based on modeling, there is always room for alternative solutions because there is usually a gap between the model and the real problem it depicts. This study looks into the problem of finding such alternative solutions, the non-optimal solutions of interest for constrained optimization models, the SoI problem. SoI problems subsume finding feasible solutions of interest (FoIs) and infeasible solutions of interest (IoIs). In all cases, the interest addressed is post-solution analysis in one form or another. Post-solution analysis of a constrained optimization model occurs after the model has been solved and a good or optimal solution for it has been found. At this point, sensitivity analysis and other questions of import for decision making come into play and for this purpose the SoIs can be very valuable. An evolutionary computation approach (in particular, a population-based metaheuristic) is proposed for solving the SoI problem and a systematic approach with a feasible-infeasible- two-population genetic algorithm is demonstrated. In this study, the effectiveness of the proposed approach on finding SoIs is demonstrated with generalized assignment problems and generalized quadratic assignment problems. Also, the applications of the proposed approach on the multi-objective optimization and robust-optimization issues are examined and illustrated with two-sided matching problems and flowshop scheduling problems respectively

Optimization Models for Locating Cross-docks under Capacity Uncertainty

The objective of this thesis is to develop mathematical models for locating cross-docks in a supply chain. Cross-docking is a strategy which can help consolidate the goods in the supply chain and save costs by reducing the number of truck trips. In this thesis four optimization models were developed. First two optimization models termed Model A and Model B were deterministic models. The goal of model A was to choose exactly P locations to locate cross-docks so that the transportation and handling costs are minimized. The goal of model B is to locate as many cross-docks as needed so that total routing, handling, and facility location costs are minimized. Then we developed a chance constraint model and a recourse model which accounted for capacity uncertainties at cross-dock location. The chance constraint model accounts for day to day operational uncertainties whereas the recourse model accounts to drastic reductions in capacities due to disruptions. Extensive computational analysis was conducted on two networks with parameters consistent with real world freight operations. The results reveal that cross-docking provides significant savings when the demand sizes are small and there is more potential for consolidation. For larger demands where the potential for consolidation is less, cross-dock savings diminish. The results were found to be consistent across a variety of capacity uncertainty scenarios

Modular Design of Physical Internet Transport, Handling and Packaging Containers

This paper proposes a three‐tier characterization of Physical Internet containers into transport, handling and packaging containers. It first provides an overview of goods encapsulation in the Physical Internet and of the generic characteristics of Physical Internet containers. Then it proceeds with an analysis of the current goods encapsulation practices. This leads to the introduction of the three tiers, with explicit description and analysis of containers of each tier. The paper provides a synthesis of the proposed transformation of goods encapsulation and highlights key research and innovation opportunities and challenges for both industry and academia

Diseño y desarrollo del modelo óptimo de asignación y cronograma de remolques en el sistema de cadena de suministro con consideración de cross dock con planificación estocástica

Todays, transportation, and logistics engineering processes are among the important issues of organizations in the competitive market. Considering the logistical structure of the logistics engineering and the more attention paid to the logistical tools and, in particular, such as the use of these tools, such as containers (pallets, containers, etc.), transportation equipment (trailer, forklift trucks, etc.), and The art of building the supply and distribution network concerning the main warehouses, cross-dock, and temporary storage, is one of the most critical and contemplative cases. In fact, all these tools work together to maximize system efficiency in the field of logistics concerning the leading impact indicators, including the time of shipment (loading, disloading, the allocation of trailers, etc.). This paper's main goal is to present and develop a mathematical model of trailer schedule planning in possible conditions in the cross-dock. In fact, the main function of this mathematical model is to minimize the total time of the logistics process from the stage of emptying the pallets from the materials producers in the cross docks and assigning the trailer to the door, and finally reloading the pallets to be distributed to the production sites. To solve this model and to analyze the outputs, mixed integer programming was used by GAMS software.Hoy en día, los procesos de ingeniería de transporte y logística se encuentran entre los temas importantes de las organizaciones en el mercado competitivo. Teniendo en cuenta la estructura logística de la ingeniería logística y la mayor atención prestada a las herramientas logísticas y, en particular, como el uso de estas herramientas, como contenedores (pallets, contenedores, etc.), equipos de transporte (remolque, carretillas elevadoras, etc.), y El arte de construir la red de suministro y distribución con respecto a los almacenes principales, cross dock y almacenamiento temporal, es uno de los casos más importantes y contemplativos. De hecho, todas estas herramientas trabajan juntas para maximizar la eficiencia del sistema en el campo de la logística con respecto a los principales indicadores de impacto, incluido el tiempo de envío (carga, descarga, asignación de remolques, etc.). El objetivo principal de este artículo es presentar y desarrollar un modelo matemático de planificación de horarios de remolques en las posibles condiciones en el muelle de cruce. De hecho, la función principal de este modelo matemático es minimizar el tiempo total del proceso logístico desde la etapa de vaciado de los pallets de los productores de materiales en los cross docks y la asignación del remolque a la puerta y finalmente la recarga de los pallets a distribuir. a los sitios de producción. Para resolver este modelo y analizar las salidas, el software GAMS utilizó la programación de enteros mixtos

Operational-level Optimization of Inbound Intralogistics

This study is concerned with optimizing inbound operations at distribution centers (DCs), warehouses, and cross-docks with staging areas. The objective of the problem is to minimize the makespan required to move all unit loads from the trailers to the flow racks, and from the flow racks to their respective storage locations. It is assumed that a set of inbound trailers with known composition have been assigned and sequenced to inbound dock doors. The following three inbound logistics decisions are simultaneously considered: i) unloaders’ assignment and scheduling, ii) loads-to-flow rack assignment, and iii) assignment and haulers’ scheduling. In this study we describe the relationship between the problem of minimizing makespan and an unloader-hauler balancing problem. Three rule-based heuristics are proposed and evaluated in an instance of the problem

Models and Algorithms for Inbound and Outbound Truck to Door Scheduling

Cross-docking is a logistic strategy that facilitates rapid movement of consolidated products between suppliers and retailers within a supply chain. It is also a warehousing strategy that aims at reducing or eliminating storage and order picking, two of which are known to be major costly operations of any typical warehouse. This strategy has been used in the retailing, manufacturing, and automotive industries. In a cross-dock, goods are unloaded from incoming trucks, consolidated according to their destinations, and then, loaded into outgoing trucks with little or no storage in between. In this thesis, we address an integrated cross-dock door assignment and truck scheduling problem in which the assignment and sequencing of incoming trucks to strip doors and outgoing trucks to stack doors is optimized to minimize the total time to process all trucks. We present a mixed integer programming formulation to model this problem and some valid inequalities to strengthen the formulation. We also present two metaheuristics to obtain high quality solutions in reasonable CPU times. These algorithms use a mix of composite dispatching rules, constructive heuristics, local search heuristics which are embedded into a greedy randomized adaptive search procedure (GRASP) and an iterated local search (ILS). Results of computational experiments are presented to assess the performance of the proposed algorithms, in comparison with a general purpose solver