Dock Assignment and Truck Scheduling Problems at Cross-docking Terminals

In this paper, we consider the integration of dock assignment and truck scheduling problem at cross-docking terminals. The problem is first formulated as a 0-1 integer programming model. Since both dock assignment and truck scheduling problems are NP-hard, its integration is more difficult to solve. Thus we propose reduced variable neighborhood search (RVNS) algorithms to solve the problem. Computational experiments are carried out on four set of instances. The results show that RVNS is capable of finding good solutions in a much shorter computation time when it is compared with optimization solver Gurobi’s solutions

Cross-docking: A systematic literature review

This paper identifies the major research concepts, techniques, and models covered in the cross-docking literature. A systematic literature review is conducted using the BibExcel bibliometric analysis and Gephi network analysis tools. A research focus parallelship network (RFPN) analysis and keyword co-occurrence network (KCON) analysis are used to identify the primary research themes. The RFPN results suggest that vehicle routing, inventory control, scheduling, warehousing, and distribution are most studied. Of the optimization and simulation techniques applied in cross-docking, linear and integer programming has received much attention. The paper informs researchers interested in investigating cross-docking through an integrated perspective of the research gaps in this domain. This paper systematically reviews the literature on cross-docking, identifies the major research areas, and provides a survey of the techniques and models adopted by researchers in the areas related to cross-docking

Scheduling Material Handling in Cross-Docking Terminals

RÉSUMÉ : La manutention au sein des plateformes de distribution est un problème d’ordonnancement. Le transport interne des produits doit en effet être synchronisé avec les arrivées et les départs des camions. Ce problème se retrouve dans toutes les plateformes de distribution où la manipulation des produits est effectuée manuellement par l’opérateur. Dans cette thèse, nous investiguons ce problème d’ordonnancement dans les plateformes de distribution. Nous mettons en relief les différentes facettes de ce problème et proposons une classification de ses différents sous problèmes. De manière générale, l'objectif est d'éviter les doubles manipulations (déplacer un produit d’un camion vers le stock, puis du stock vers un camion) qui doublent les coûts sans valeur ajoutée. Il faut minimiser ces doubles manipulations en orchestrant les transferts internes et la séquence de chargement/ déchargement des camions. Dans une première partie, nous analysons la structure du problème avec un modèle simplifié n’ayant qu’un quai de réception et un quai d’envois. Nous formalisons les décisions de manipulation interne et développons un algorithme optimal pour déterminer le meilleur plan de transfert de produits lorsque la séquence des camions est connue. Cet algorithme est utilisé comme fonction d’évaluation dans une recherche stochastique pour minimiser les doubles manipulations et optimisant les séquences de chargement/déchargement. Nous présentons ensuite un modèle de programmation linéaire en nombres entiers du problème général (ordonnancement des arrivées et départs de camions et transfert interne des produits). Nous proposons un algorithme de séparation et d’évaluation permettant une résolution efficace du problème. Nous proposons des structures de dominance et quelques inégalités valides permettant d’améliorer les performances de l’algorithme. Cette approche nous permet de résoudre à l’optimum en un temps raisonnable de très gros problèmes. Dans une seconde partie, nous étendons ces modèles au problème général avec plusieurs quais. Nous nous intéressons d’abord au terminal de type satellite où l’ordonnancement des camions d’entrée est connu. Ces plateformes opèrent en deux mouvements différents : l’ordonnancement et chargement pour le transport de nuit et celui pour les livraisons matinales. Nous donnons une représentation mathématique qui permet de résoudre les problèmes de petite taille. Pour ceux de plus grandes ampleurs, nous utilisons une heuristique. Les résultats numériques montrent la validité de cette approche. Finalement, nous généralisons le type de plateforme (les séquences d’arrivée et de départ sont à déterminer) et développons un nouveau modèle d’ordonnancement plus compact. Nous utilisons pour les grandes instances une recherche par voisinage. Nous mettons en place des voisinages originaux adaptés à ce type d’ordonnancement. Mots clés: Transfert de produits, ordonnancement, plateforme de transbordement, recherche stochastique, programmation à nombres entiers, heuristiques, recherche du plus proche voisin.----------ABSTRACT : Material handling in cross-dock is a relevant class of scheduling problems in distribution centers in which inner transhipment decisions need to be considered in addition to the processing order of trucks. The problem has applications in distribution centers where operators manually perform internal transhipment. In this dissertation, we investigate the problem of material handling inside cross-docking terminals. The main component of the problem is presented, followed by a classification scheme to express its diversity. Moreover, double handling identifies the main source of deficiencies in transferring operations. The objective is to synchronize the trucks’ loading and unloading sequences with internal transferring decisions to minimize excessive product displacement inside the terminal. First, the problem is studied for a conceptual model of the platform with single receiving and shipping doors. We formalize decisions on internal transhipment and develop an algorithm to determine the best transferring plan with restricted orders on processing trucks. This algorithm is employed as an evaluation function in a stochastic search framework to ameliorate the order of processing trucks and reduce the cost of double handling. Then, a mixed integer linear programming formulation of the general problem is introduced. The proposed model determines the joint schedule between processing order of trucks at inbound and outbound doors with an internal transhipment plan. A path branching algorithm is proposed. We present several structural properties and some valid inequalities to enhance the performance of the algorithm. This method could solve fairly large instances within a reasonable time. Second, we extend the developed models and approaches to schedule material handling process for a real platform with multiple doors. In the first installment, we focus on the satellite cross-docks that have limitations on the processing order of trucks at inbound door. These platforms operate in two separate shifts: consolidating pickup freight for overnight shipments and processing received products for early morning deliveries. A mathematical formulation of the problem is presented that can solve small instances with commercial software. In addition, a sequential priority-based heuristic is introduced to tackle the large problems. Numerical results depict the stability of this approach. Finally, in the second instalment, we study the general model with no restriction on the arrival and departure pattern of trucks and formulate a new mathematical model. This model has considerably fewer variables and constraints than the previous one. Moreover, a variable neighborhood search heuristic is developed to tackle real life problems. This method consists of several operators incorporated in a search subroutine to find local optima and a perturbation operator to alter it. The developed method is adopted for three scenarios concerning limitations imposed by the network schedule. The analyzes demonstrate economical savings in the cost of material handling. Keywords: Material handling; scheduling; cross-dock; stochastic search; Integer programming; heuristic; variable neighborhood search

High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization

Disertační práce je zaměřena na optimalizaci průběhu pracovních operací v logistických skladech a distribučních centrech. Hlavním cílem je optimalizovat procesy plánování, rozvrhování a odbavování. Jelikož jde o problém patřící do třídy složitosti NP-težký, je výpočetně velmi náročné nalézt optimální řešení. Motivací pro řešení této práce je vyplnění pomyslné mezery mezi metodami zkoumanými na vědecké a akademické půdě a metodami používanými v produkčních komerčních prostředích. Jádro optimalizačního algoritmu je založeno na základě genetického programování řízeného bezkontextovou gramatikou. Hlavním přínosem této práce je a) navrhnout nový optimalizační algoritmus, který respektuje následující optimalizační podmínky: celkový čas zpracování, využití zdrojů, a zahlcení skladových uliček, které může nastat během zpracování úkolů, b) analyzovat historická data z provozu skladu a vyvinout sadu testovacích příkladů, které mohou sloužit jako referenční výsledky pro další výzkum, a dále c) pokusit se předčit stanovené referenční výsledky dosažené kvalifikovaným a trénovaným operačním manažerem jednoho z největších skladů ve střední Evropě.This work is focused on the work-flow optimization in logistic warehouses and distribution centers. The main aim is to optimize process planning, scheduling, and dispatching. The problem is quite accented in recent years. The problem is of NP hard class of problems and where is very computationally demanding to find an optimal solution. The main motivation for solving this problem is to fill the gap between the new optimization methods developed by researchers in academic world and the methods used in business world. The core of the optimization algorithm is built on the genetic programming driven by the context-free grammar. The main contribution of the thesis is a) to propose a new optimization algorithm which respects the makespan, the utilization, and the congestions of aisles which may occur, b) to analyze historical operational data from warehouse and to develop the set of benchmarks which could serve as the reference baseline results for further research, and c) to try outperform the baseline results set by the skilled and trained operational manager of the one of the biggest warehouses in the middle Europe.

Application of Tabu Search to Scheduling Trucks in Multiple Doors Cross-Docking Systems

RÉSUMÉ : Cette recherche focus sur l’amélioration des cross-dockings en vue d’augmenter les niveaux de performance du service et de réduire les coûts. l’algorithme de la recherche avec tabous est étudiée pour trouver la séquence optimale d’entrée et sortie des remorques au cross-docking. L’objectif de cette recherche est de maximiser le nombre total de transferts directs entre le fournisseur et une destination finale commune de livraison. Dans les stratégies de distribution actuelles, l’objectif est de synchroniser les chaines du fabricant et du client. Le cross-docking implique de recevoir les produits d’un fournisseur pour plusieurs clients et d’occasionnellement consolider cela avec les produits d’autres fournisseurs pour des destinations finales de livraison communes. En résumé, l’approche examinée dans cette recherche donne une occasion significative pour l’amélioration des opérations au Cross-docking par la réduction du stockage des produits.----------ABSTRACT : Today’s supply chain management performance has been affected by continuously increasing pressure of market forces. The pressure of market includes demands on increased flow of products and throughput with less amount of storage, also customers demand for more products with lower operational costs and more value-added services provided to customers. Supply chain is responsible in cost reduction and service levels increase by providing transshipments across its members. However supply chain has to face fluctuations of demands with the short available lead times. Physical problem of warehouse limitations and also inventory costs and shipping affect the performance of supply chain. In today’s distribution strategies, the main goal is to provide a synchronization of customer chains and the suppliers. The objective is to reduce the inventory buffering between customers and suppliers. The idea of cross-docking is to receive different goods from a manufacturer for several end destinations and possibly consolidate the goods with other manufacturer’s items for common final customers; then ship them in the earliest possible time. The focus of this research effort is to improve cross-dock operations with the goal of increasing the service performance levels and reducing costs. Specifically, metaheuristics algorithm of Tabu search is investigated for finding optimal sequence of incoming and outgoing trailers at cross-docks. This thesis reviews available research literature on cross-dock operations. Tabu search for the truck scheduling problem is presented along with results. Tabu search algorithm is investigated for the truck scheduling problem in the multiple doors cross-docking with unknown incoming and outgoing sequences. The objective of this research is to maximize the total direct transfer of products from a supplier to common final delivery destinations. The algorithm is implemented in C++ and analyzed using different problem instances. The results gained from algorithm of Tabu search are compared with other iterative heuristic descent method. The results indicate that the Tabu search performs significantly better than the descent method for large problem instances. In general, the results present that a metaheuristic algorithm of Tabu search for multiple or single door cross-docking offers thelargest potential for improvement. In summary, the approach explored in this research offers significant opportunity to improve cross-dock operations through reducing storage of products

Scheduling cross-docking operations under uncertainty: A stochastic genetic algorithm based on scenarios tree

A cross-docking terminal enables consolidating and sorting fast-moving products along supply chain networks and reduces warehousing costs and transportation efforts. The target efficiency of such logistic systems results from synchronizing the physical and information flows while scheduling receiving, shipping and handling operations. Within the tight time-windows imposed by fast-moving products (e.g., perishables), a deterministic schedule hardly adheres to real-world environments because of the uncertainty in trucks arrivals. In this paper, a stochastic MILP model formulates the minimization of penalty costs from exceeding the time-windows under uncertain truck arrivals. Penalty costs are affected by products' perishability or the expected customer’ service level. A validating numerical example shows how to solve (1) dock-assignment, (2) while prioritizing the unloading tasks, and (3) loaded trucks departures with a small instance. A tailored stochastic genetic algorithm able to explore the uncertain scenarios tree and optimize cross-docking operations is then introduced to solve scaled up instaces. The proposed genetic algorithm is tested on a real-world problem provided by a national delivery service network managing the truck-to-door assignment, the loading, unloading, and door-to-door handling operations of a fleet of 271 trucks within two working shifts. The obtained solution improves the deterministic schedule reducing the penalty costs of 60%. Such results underline the impact of unpredicted trucks’ delay and enable assessing the savings from increasing the number of doors at the cross-dock

Managing Advanced Synchronization Aspects in Logistics Systems

In this thesis, we model various complex logistics problems and develop appropriate techniques to solve them. We improve industrial practices by introducing synchronized solutions to problems that were previously solved independently. The first part of this thesis focuses on cross-docks. We simultaneously optimize supplier orders and cross-docking operations to either reduce the storage space required or evenly distribute workload over the week. The second part of this thesis is devoted to transport problems in which two types of vehicles are synchronized, one of which can be transported by the other. The areas of application range from home services to parcel delivery to customers. After analyzing the complexity associated with these synchronized solutions (i.e., largescale problems for which the decisions depend on each other), we design algorithms based on the "destroy-and-repair" principle to find efficient solutions. We also introduce mathematical programs for all the considered problems. The problems under study arose directly from collaborations with various industrial partners. In this respect, our achieved solutions have been benchmarked with current industrial practice. Depending on the problem, we have been able to reduce the environmental impact generated by the industrial activities, the overall cost, or the social impact. The achieved gains compared to current industrial practice range from 10 to 70%, depending on the application. -- Dans cette thèse, nous modélisons divers problèmes logistiques complexes et développons des techniques appropriées pour les résoudre. Nous cherchons à améliorer certaines pratiques industrielles en introduisant des solutions synchronisées à des problèmes qui étaient auparavant résolus indépendamment. La première partie de cette thèse porte sur les cross-docks. Nous optimisons simultanément les commandes fournisseurs et les opérations au sein de la plateforme de logistique pour réduire l’espace de stockage requis ou répartir uniformément la charge de travail sur la semaine. La deuxième partie de cette thèse est consacrée aux problèmes de transport dans lesquels deux types de véhicules sont synchronisés, l’un pouvant être transporté par l’autre. Les domaines d’application vont du service à domicile à la livraison de colis chez des clients. Après avoir analysé la complexité des solutions synchronisées (c’est-à-dire des problèmes de grandes dimensions pour lesquels les décisions dépendent les unes des autres), nous concevons des algorithmes basés sur le principe de "destruction / reconstruction" pour trouver des solutions efficaces. Nous modélisons également les problèmes considérés avec la programmation mathématique. Les problèmes à l’étude viennent de collaborations avec divers partenaires industriels. A cet égard, les solutions que nous présentons sont comparées aux pratiques industrielles actuelles. En fonction du problème, nous avons pu réduire l’impact environnemental généré par les activités industrielles, le coût global, ou l’impact social des solutions. Les gains obtenus par rapport aux pratiques industrielles actuelles varient de 10 à 70%, selon l’application. Mot-clefs: Logistique, Synchronisation, Problème de transport, Tournée de véhicules, Plateforme de Cross-dock (transbordement), Programmation Mathématiques, Métaheuristiques, Matheuristiques, Instances Réelle

Heuristics for Truck Scheduling at Cross Docking Terminals

Cross-docking is a logistics management concept that has been gaining global recognition in less-than-truckload logistics industries and retail firms. In cross-docking terminals, shipments are unloaded from inbound trucks at strip doors, consolidated insider cross-docks according to their destinations, and then, loaded into outbound tucks at stack doors. The goal of cross-docking is to reduce inventory and order picking which are the two most costly functions of traditional warehousing management. The sequence in which the inbound and outbound trucks have to be processed at the cross-dock is crucial for improving the efficiency of cross-docking systems. In this thesis we introduce an integer programming formulation and apply four heuristic algorithms: a local search, a simulated annealing, a large neighborhood search and a beam search, to schedule the trucks in a cross-docking terminal so as to minimize the total operational time

Truck scheduling problem in a cross-docking system with release time constraint

Abstract In a supply chain, cross-docking is one of the most innovative systems for ameliorating the operational performance at distribution centers. Cross-docking is a logistical strategy in which freight is unloaded from inbound trucks and (almost) directly loaded into outbound trucks, with little or no storage in between, thus no inventory remains at the distribution center. In this study, we consider the scheduling problem of inbound and outbound trucks with multiple dock doors, aiming at the minimization of the makespan. The considered scheduling problem determines where and when the trucks must be processed; also due to the interchangeability specification of products, product assignment is done simultaneously as well. Inbound trucks enter the system according to their release times', however, there is no mandatory time constraint for outbound truck presence at a designated stack door; they should just observe their relative docking sequences. Moreover, a loading sequence is determined for each of the outbound trucks. In this research, a mathematical model is derived to find the optimal solution. Since the problem under study is NP-hard, a simulated annealing algorithm is adapted to find the (near-) optimal solution, as the mathematical model will not be applicable to solve largescale real-world cases. Numerical examples have been done in order to specify the efficiency of the metaheuristic algorithm in comparison with the results obtained from solving the mathematical model

Cross-Docking: A Proven LTL Technique to Help Suppliers Minimize Products\u27 Unit Costs Delivered to the Final Customers

This study aims at proposing a decision-support tool to reduce the total supply chain costs (TSCC) consisting of two separate and independent objective functions including total transportation costs (TTC) and total cross-docking operating cost (TCDC). The full-truckload (FT) transportation mode is assumed to handle supplier→customer product transportation; otherwise, a cross-docking terminal as an intermediate transshipment node is hired to handle the less-than-truckload (LTL) product transportation between the suppliers and customers. TTC model helps minimize the total transportation costs by maximization of the number of FT transportation and reduction of the total number of LTL. TCDC model tries to minimize total operating costs within a cross-docking terminal. Both sub-objective functions are formulated as binary mathematical programming models. The first objective function is a binary-linear programming model, and the second one is a binary-quadratic assignment problem (QAP) model. QAP is an NP-hard problem, and therefore, besides a complement enumeration method using ILOG CPLEX software, the Tabu search (TS) algorithm with four diversification methods is employed to solve larger size problems. The efficiency of the model is examined from two perspectives by comparing the output of two scenarios including; i.e., 1) when cross-docking is included in the supply chain and 2) when it is excluded. The first perspective is to compare the two scenarios’ outcomes from the total supply chain costs standpoint, and the second perspective is the comparison of the scenarios’ outcomes from the total supply chain costs standpoint. By addressing a numerical example, the results confirm that the present of cross-docking within a supply chain can significantly reduce total supply chain costs and total transportation costs