Cross-dock Facility Research Articles

Routing vehicles through cross-docking facility for third party logistics service providers

Routing vehicles through cross-docking facility for third party logistics service providers

The impact of collection portfolio expansion on key performance indicators of the Dutch recycling system for Post-Consumer Plastic Packaging Waste, a comparison between 2014 and 2017

The recycling network of post-consumer plastic packaging waste (PCPPW) was studied for the Netherlands in 2017 with material flow analysis (MFA) and data reconciliation techniques. In comparison to the previous MFA of the PCPPW recycling network in 2014, the predominant change is the expansion of the collection portfolio from only plastic packages to plastic packages, beverage cartons and metal objects. The analysis shows that the amounts of recycled plastics products (as main washed milled goods) increased from 75 to 103 Gg net and the average polymeric purity of the recycled products remained nearly constant. Furthermore, the rise in the amounts of recycled products was accompanied with a rise in the total amount of rejected materials at cross docking facilities and sorting residues at the sorting facilities. This total amount grew from 19 Gg in 2014 to 70 Gg gross in 2017 and is over-proportional to the rise in recycled products. Hence, there is a clear trade-off between the growth in recycled plastics produced and the growth in rejects and residues. Additionally, since the polymeric purity of the recycled plastics did not significantly improve during the last years, most of the recycled plastics from PCPPW are still only suited for open-loop recycling. Although this recycling system for PCPPW is relatively advanced in Europe, it cannot be considered circular, since the net recycling yield is only 26 ± 2% and the average polymeric purity of the recycled plastics is 90 ± 7%.

A truck scheduling problem at a cross-docking facility with mixed service mode dock doors

PurposeThe purpose of this study is truck scheduling and assignment of trucks to the doors simultaneously since these issues were considered mainly separately in the previous research. Also, the door service time and its impact on truck scheduling were not taken into account, so this research endeavors to cover this gap.Design/methodology/approachIn this research, a novel model has been presented for simultaneous truck scheduling and assignment problem with time window constraints for the arrival and departure of trucks, mixed service mode dock doors and truck queuing. To resolve the developed model, two meta-heuristic algorithms, namely, genetic and imperialist competitive algorithms, are presented.FindingsThe computational results indicate that the proposed framework leads to increased total costs, although it has a more accurate planning; moreover, these indicate that the proposed algorithms have different performances based on the criteria considered for the comparison.Research limitations/implicationsThere are some limitations in this research, which can be considered by other researchers to expand the current study, among them the specifications of uncertainty about arrival times of inbound and outbound trucks, number of merchandises which has been loaded on inbound trucks are the main factors. If so, by considering this situation, a realistic scheme about planning of cross docking system would be acquired. Moreover, the capacity of temporary storage has been considered unlimited, so relaxing this limitation can prepare a real and suitable situation for further study. Examining the capacity in the front of each type of doors of cross-dock and executive servers are the other aspects, which could be expanded in the future.Originality/valueIn this study, a mathematical programing model proposed for truck scheduling to minimize total costs including holding, truck tardiness and waiting time for queue of trucks caused by the interference of each carrier’s movement. At the operational levels, this research considered a multi-door cross-docking problem with mixed service mode dock doors and time window constraints for arrival and departure time of trucks. Moreover, M/G/C queue system was developed for truck arrival and servicing of carriers to trucks.

Integrated scheduling and assignment of trucks at unit-load cross-dock terminals with mixed service mode dock doors

Scheduling trucks and assigning them to dock doors are two major operational decisions at cross-dock facilities. Including flexibility by operating (part of) the dock doors in a mixed service mode is known to make cross-dock operations more efficient (i.e., when both inbound and outbound trucks can be processed at these mixed-mode doors). However, the literature and practice often consider the truck scheduling and dock-door assignment problem sequentially, or only for either inbound or outbound operations. When combined with mixed-mode dock doors, such a sequential approach results in suboptimal or even infeasible solutions. In this paper, we study an integrated approach to solve the two problems simultaneously for cross-dock terminals where dock doors can operate in a mixed service mode. We propose an adaptive large neighborhood search algorithm to solve the integrated problem and find good solutions within a reasonable amount of computational effort. Extensive computational experiments demonstrate that the operational costs at a cross-dock terminal reduce on average 12% compared to the best solution with a sequential approach (and even 20–30% compared to the results of the metaheuristics from the literature). Moreover, with the integrated approach, we study what percentage of dock doors to operate in a mixed service mode and where to position these flexible doors in U-shaped cross-dock terminals. Numerical results indicate an average cost savings of 9.7% when 60% of the dock doors are used flexibly, and the savings increase to 12.3% when these doors are centrally located in the cross-dock facility.

A comparative study of formulations for a cross-dock door assignment problem

A cross docking facility is a type of warehouse in supply chain management that allows orders to be prepared with or without going through the phase of storing products in the warehouse and subsequently selecting them for delivery. The goods are unloaded from incoming trucks called origins on inbound doors of a cross-docking facility platform and, using a handling device inside the platform such as a forklift, immediately transferred to outbound doors to be loaded into outgoing trucks named destinations or delivery trucks for distribution to customers. Contrary to a traditional warehouse, goods are unloaded and loaded without placing them in temporary storage inside the cross-docking facility. The goal of the cross-docking assignment problem (CDAP) is to assign origins to inbound doors and destinations to outbound doors so that the total cost inside the cross-dock platform is minimized. To the best of our knowledge, there are only three mixed integer programming (MIP) formulations of the CDAP in the literature. We propose eight new MIP models and demonstrate the mathematical equivalence of all 11 models, together with rigorously proving some of their properties. In order to detect which of these 11 models is best, we conduct an extensive comparative analysis on benchmark instances from the literature, which discloses that the best model is one proposed in this paper for the first time.

A Diploid Evolutionary Algorithm for Sustainable Truck Scheduling at a Cross-Docking Facility

Supply chains have become more time-sensitive in recent years. Delays in supply chain operations may cause significant negative externalities, including lost sales and customers. In order to facilitate the product distribution process within supply chains, reduce the associated delays, and improve sustainability of the supply chain operations, many distribution companies started implementing the cross-docking technique. One of the challenging problems in management of the cross-docking facilities is efficient scheduling of the arriving trucks. This study proposes a novel Diploid Evolutionary Algorithm for the truck scheduling problem at a cross-docking facility, which—unlike the Evolutionary Algorithms presented in the cross-docking literature to date—stores the genetic information from the parent chromosomes after performing a crossover operation. The objective of the formulated mathematical model is to minimize the total truck service cost. The conducted numerical experiments demonstrate that the optimality gap of the developed algorithm does not exceed 0.18% over the considered small size problem instances. The analysis of the realistic size problem instances indicates that deployment of the developed solution algorithm reduces the total truck handling time, the total truck waiting time, and the total truck delayed departure time on average by 6.14%, 32.61%, and 34.01%, respectively, as compared to a typical Evolutionary Algorithm. Furthermore, application of the diploidy concept decreases the total truck service cost by 18.17%.

Vehicle routing and scheduling in cross docks with forward and reverse logistics

Cross-docking is a useful logistic practice used by many companies to reduce logistical costs. Cross-docking facilities are responsible for transferring products from suppliers to retailers and vice versa. Furthermore, vehicle routing is an important issue with regard to cross-docks. This paper investigates, for the first time, a vehicle routing problem in a distribution network with a cross-docking center by considering both forward and reverse logistics in an integrated model. In this regard, two strategies are presented to tackle the forward and reverse logistics. A mathematical model is developed for each strategy in order to find the best solution to transfer products from suppliers to retailers and then return products from retailers to suppliers through cross docks with minimum transportation cost. As the resulting mathematical model is NP-hard, a simulated annealing based heuristic algorithm is developed to optimize the model. Finally, these strategies are compared in terms of cost and the results demonstrate that the second strategy is superior to the first one.

Location-Allocation and Scheduling of Inbound and Outbound Trucks in Multiple Cross-Dockings Considering Breakdown Trucks

This paper studies multiple cross-dockings where the loads are transferred from origins (suppliers) to destinations (customers) through cross-docking facilities. Products are no longer stored in intermediate depots and incoming shipments are consolidated based on customer demands and immediately delivered to them to their destinations. In this paper, each cross-docking has a covering radius that customers can be served by at least one cross-docking provided. In addition, this paper considers the breakdown of trucks. We present a two-stage model for the location of cross-docking centers and scheduling inbound and outbound trucks in multiple cross-dockings.We work on minimizing the transportation cost in a network by loading trucks in the supplier locations and route them to the customers via cross-docking facilities. The objective, in the first stage, is to minimize transportation cost of delivering products from suppliers to open cross-docks and cross-docks to the customers; in the second-stage, the objective is to minimize the makespans of open cross-dockings and the total weighted summation of completion time. Due to the difficulty of obtaining the optimum solution tomedium- and large-scale problems, we ‌propose four types of metaheuristic algorithms, i.e., genetic, simulated annealing, differential evolution, and hybrid algorithms.The result showed that simulated annealing is the best algorithm between the four algorithms.

Dynamic Models for Supply Chain Planning in Oilfield Services Industry: A Case for Hybrid Cross-Docks

We consider a supply chain planning problem via efficient cross-docking for oilfield services industry. The problem is motivated from a major oilfield services company in North America. In a typical supply chain setup of this industry, the companies ship raw materials to an international location (typically a Free Trade Zone), which serves as the stock consolidation point for the region, break-bulk and then ship to field locations (oil excavation sites also called plants). In this research, the consolidation points are hybrid cross-docks (HCD), where raw materials can be stored free of cost for a specific period of time. The supply chain problem involves minimizing the total inbound and outbound transportation costs and the inventory management costs at the cross-docking facility and the plants. In this context, we analyze two problems under the following scenarios: (i) all raw-materials required at each plant (outbound delivery) are shipped periodically by the company from the HCD, and (ii) the outbound delivery is outsourced to a 3PL. For the first problem, we perform complexity analysis, use discrete optimization, and develop a heuristic algorithm. For the second problem, we perform stochastic analysis and robust optimization. The first scenario gives rise to new integrated inventory and logistics models. The second scenario provides new theoretical models and analysis for a variation of the dynamic lot-sizing problem. This paper demonstrates the use of a modeling approach that not only meets this need for this specific industry, but also has the potential to be applied to other industries with similar supply chain structure.

A mathematical model for truck-door assignment and product placement problem in cross-docking center

In today's cross-docking offers a significant cost benefits to companies because of the small orders and frequent deliveries in logistical environment. Cross-docking is a relatively new logistics strategy in which items are moved from suppliers to customers through cross-docking centers without putting them into long-term storage. One of the fundamental issues in cross-docking facility is to assign the incoming and outgoing trucks to the doors in order to minimize movement of the products. This paper addresses the truck-door assignment problem of cross-docking centers with product placement plans and proposes a mixed integer mathematical model to solve problem. The objective of the mathematical model is to find best truck-door assignment and product placement plans that minimize total travelling distance of the products. The proposed model is tested on a problem set which are created by using a real-life data of a logistics company. The computational results show that the proposed mathematical model can be carried out for the real-life operations to minimize movement costs of the products in cross-docking centers. Keywords: Cross-docking, truck-door assignment, product placement, mathematical modelling;

Bi-objective optimization of a three-echelon multi-server supply-chain problem in congested systems: Modeling and solution

A novel bi-objective three-echelon supply chain problem is formulated in this paper in which cross-dock facilities to transport the products are modeled as an M/M/m queuing system. The proposed model is validated using the epsilon constraint method when applied to solve some small-size problems. Since the problem belongs to the class of NP-hard and that it is of a bi-objective type, a multi-objective particle swarm optimization (MOPSO) algorithm with a new solution structure that satisfies all of the constraints is developed to find Pareto solutions. As there is no benchmark available in literature, three other multi-objective meta-heuristic algorithms called non-dominated ranking genetic algorithm (NRGA), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective imperialist competitive algorithm (MOICA) are utilized as well to validate the solutions obtained for large-scale problems. The parameters of the solution algorithms are calibrated using the Taguchi method. The comparison results based on five multi-objective performance metrics used in the AHP-TOPSIS method show that the parameter-tuned MOPSO acts better than the other parameter-tuned algorithms to solve, small, medium, and large-size problems.

Moving products between location pairs: Cross-docking versus direct-shipping

This work considers the problem of satisfying transportation requests from a set of suppliers to a set of customers. Each request calls for moving products between a pick-up and a delivery location pair. A commonly adopted approach is the direct-shipping of products, without using intermediate transshipment points, or in-transit merge of shipments. Another alternative strategy that often appears in practice is to use an intermediate cross-dock facility, acting as a consolidation point for transported products. The goal of this paper is to evaluate these inherently different distribution options and to conduct a comprehensive comparative analysis regarding their cost-effectiveness. For this purpose, a local-search optimization framework has been developed. The optimization framework is tested on existing, as well as new benchmark data sets. Various computational experiments have been performed, to analyze the impact of several spatial and temporal characteristics, such as the geographic distribution of customers and suppliers, the proximity of individual pick-up and delivery pairs, the positioning of the depot, the tightness of the capacity and duration constraints, and the time required to handle and consolidate shipments at the cross-dock. The results of the computational experiments are further analyzed through a logistic regression analysis, in order to identify the characteristics that affect the relative effectiveness of the two compared strategies. In addition, a mixed model considering both direct-shipping and cross-docking is tackled by appropriately extending the proposed local-search framework.

Time-indexed formulation and polynomial time heuristic for a multi-dock truck scheduling problem in a cross-docking centre

Cross-docking is a logistic solution bringing significant cost reductions and simplifying operations of distribution centres. The success of this strategy relies on an efficient transhipment operation. This article undertakes a study of truck scheduling in a cross-docking facility. The problem is formulated as a two-stage hybrid flow-shop problem, subject to cross-docking constraints with the objective of minimising the makespan. We propose a time-indexed mixed integer linear programming formulation and a polynomial time heuristic. Results show that the heuristic outperformed current results in the literature for moderate and large size instances.

Modeling truck scheduling problem at a cross-dock facility through a bi-objective bi-level optimization approach

Uncertainty and non-deterministic nature of the real world makes planning and scheduling in cross-docks a very complicated task for decision makers. These constant changes that happen all the time, often, lead to an increase in costs and/or a decrease in efficiency. Most of the uncertainty in cross-docks is caused by un-known truck arrival times. In this study we address the problem of scheduling incoming and outgoing trucks at a cross-dock facility, when vehicle arrival times are unknown, through a cost-stable scheduling strategy. Two meta-heuristics, MODE and NSGA-II, are used for solving the designed sample problems and are compared with a random search based genetic algorithm existing in the literature. Finally, performance of each algorithm is measured and analyzed using four metrics: quality, spacing, diversification and mean ideal distance. The results indicate that the proposed model MODE algorithm performs better in comparison with the other two methods.

A solution framework for the multi-mode resource-constrained cross-dock scheduling problem

In this paper we propose a framework for shift-level container scheduling and resource allocation decisions at a cross-dock facility. The Multi-Mode Resource-Constrained Cross-Dock Scheduling Problem (MRCDSP) approach minimizes material flow and schedules inbound and outbound containers to dock-doors such that the total processing time is minimized subject to the resource constraints at the cross-dock. While container scheduling and resource allocation problems at cross-dock facilities have been studied previously in isolation, our work is the first to consider a complete view of cross-dock operations providing optimal container to dock-door allocation, and a makespan minimizing schedule of containers to the cross-dock. We present a comprehensive framework that includes identification of container clusters to reduce the problem size, a container-to-dock-door assignment algorithm, and a container clusters scheduling model that is solvable for practically sized problems. In a comparative numeric study based on data simulating a cross-dock facility, our approach is shown to outperform current practice, reducing the average time required for processing a set of containers by 37% and reducing the weighted-distance material traveled within the cross-dock by 45%.

A branch-and-price approach to evaluate the role of cross-docking operations in consolidated supply chains

Supply-chain management and optimization aims at reducing costs and inventories. One way to increase the supply-chain efficiency is to use cross-docking for consolidating shipments from different suppliers. Cross-docking is a warehousing strategy used in logistics that consists on moving goods from suppliers to customers through a cross-dock facility. The employment of this strategy must be carefully evaluated because sometimes transportation requests can be better directly moved from source-sites to destination. A realistic problem studying the convenience of direct delivery, avoiding some cross-docking transfers, is here discussed. An efficient methodology for finding (near)optimal solutions is also described. The methodology is based on the use of column generation embedded into an incomplete branch-and-price tree. The approach provides (near)optimal solutions by solving the column generation sub-problems without necessarily considering all unexplored nodes in the search-tree. Finally, we show computational results on numerous test problems and on four configurations of the addressed case study.

A novel multi-objective meta-heuristic model for solving cross-docking scheduling problems

Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This process minimizes the storage and order-picking functions in a warehouse. In this paper, we consider cross-docking in a supply chain and propose a multi-objective mathematical model for minimizing the make-span, transportation cost and the number of truck trips in the supply chain. The proposed model allows a truck to travel from a supplier to the cross-dock facility and from the supplier directly to the customers. We propose two meta-heuristic algorithms, the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective particle swarm optimization (MOPSO), to solve the multi-objective mathematical model. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example. The numerical results show the relative superiority of the NSGA-II method over the MOPSO method.

The Role of Logistics Service Providers in Supply Chain Performance Management: A comprehensive Literature Review

Logistics activities cover the entire supply chain so they become important in improving supply chain’s overall performance. The target of logistics process is to merge and organize all activities involved in acquiring, converting and distributing goods from raw materials to finished goods to the customers in order to achieve customer service objectives in an efficient cost effective manner. The logistics services providers can also enhance the supply chain activity through the introduction and induction of cross docking facilities. These new facilities not only have the potential to eradicate useless and unnecessary stock of inventories but can also boost the customer service quality through distribution network redesigning. Every company within the supply chain conducts their business activities in their own way. So the sharing of sensitive information between the supply chain partners, and monitoring of activities other than the companies own shareholders and stakeholders are act as hinders in the whole process.

Optimal Design of the Cross-docking in Distribution Networks: Heuristic Solution Approach

Cross-docking plays an importation role in distribution networks. In the recent years, a cross-docking design network problem is addressed as a new research area in logistics management. This paper presents a new mathematical model for the location of cross-docking facilities and vehicle routing scheduling problems in the distribution networks. For this purpose, a two-phase mixed-integer programming (MIP) is formulated. Then, a new heuristic-based simulated annealing (SA) is developed for solving the proposed MIP model. Finally, the presented heuristic algorithm is subsequently tested on a number of small and large-scale instances. The computational results for different-sized instances illustrate that the proposed algorithm performs effectively in a reasonable time.

A monolithic approach to vehicle routing and operations scheduling of a cross-dock system with multiple dock doors

Cross-docking is a logistic strategy for moving goods from suppliers to customers via a cross-dock terminal with no permanent storage. The operational planning of a cross-dock facility involves different issues such as vehicle routing, dock door assignment and truck scheduling. The vehicle routing problem seeks the optimal routes for a homogeneous fleet of vehicles that sequentially collects goods at pickup points and delivers them to their destinations. The truck scheduling problem deals with the timing of unloading and reloading operations at the cross-dock. This work introduces a mixed-integer linear programming formulation for the scheduling of single cross-dock systems that, in addition to selecting the pickup/delivery routes, simultaneously decides on the dock door assignment and the truck scheduling at the cross-dock. The proposed monolithic formulation is able to provide near-optimal solutions to medium-size problems involving up to 70 transportation orders, 16 vehicles and 7 strip/stack dock doors at acceptable CPU times.