Cross-docking Terminals Research Articles

Open vehicle routing problem with moving shipments at the cross-docking terminal

In this study, one of the internal operations at the Cross-docking Terminal (CDT), moving shipments (MS) from receiving doors to shipping doors of CDT is integrated with Open Vehicle Routing Problem (OVRP) and the problem is indicated here as OVRPCD-MS. As an additional feature, asymmetric distance between any two customers is assigned by incorporating a characteristic of one-way routes between cities in real-life transportation. The objective is to minimize the total transportation cost which incurs travelling cost between customers, service cost at customer points, service cost at the receiving and shipping doors of CDT, cost of moving shipments inside the CDT and finally the cost of hiring fleets of vehicles. To solve the OVRPCD-MS problem, a Mixed Integer Linear Programming (MILP) model is developed. The programming models are implemented in LINGO (version 18) optimization software. Branch and Bound algorithm is employed to solve ten small-scale instances generated randomly. The applicability of the proposed MILP model is observed. The required fleets of vehicles to be hired and run time to reach the optimal solution are determined. The study revealed that the average run time is exponential for small-scale instances. Thus, it can be concluded that this proposed model can be used for last time planning for small-scale instances. Also, the combinatorial nature of the vehicle routing problem makes OVRPCD-MS as NP-hard. Therefore, this study recommends that heuristic or meta-heuristic methods are more appropriate for the large-scale instances of OVRPCD-MS to reach near-optimum solutions.

An optimization model for forklift utilisation and congestion control in cross-docking terminals

This study aims to optimize cross-docking (CD) performance and efficiency in CD assignment problems by maximising forklift utilisation inside the terminal. ‘We present a new Mixed-Integer Nonlinear programming (MINLP)’ model that considers truck-door assignment and forklift utilisation inside the airport. One objective is to enhance the quality of truck-door by minimising the total transshipment costs, including the penalty cost associated with forklift underutilisation, the total forklift travel distance cost, and the total weighted loading unloading and operator cost. Another objective is to control the forklift congestion by minimising the total number of forklifts needed to transfer products between multiple doors inside the terminal. Two algorithms, including the tabu-search and the best-local-point-finder, are proposed to accomplish these objectives. Our computational results show the advantage of the proposed algorithms over the CPLEX commercial solver.

Selective Strategy Differential Evolution for Stochastic Internal Task Scheduling Problem in Cross-Docking Terminals.

This study proposed an algorithm called selective strategy differential evolution (SSDE) to handle the complexity of the stochastic internal task scheduling problem in cross-docking terminals. The aims of this study are to assign workers and transfer equipment to internal operations and sequence those operations under randomness and uncertainty with the purpose to minimise total tardiness. The main feature of SSDE is its ability to adapt itself in order to execute the best search strategy. The proposed algorithm was tested on 16 instances using generated data based on real-case scenarios of a pharmaceutical distribution centre. The results showed the significant performance of SSDE to other existing algorithms in terms of solution quality and computational time. The key success factors of SSDE are the use of various search strategies in a single run and the application of suitable termination conditions.

Truck scheduling optimization at a cold-chain cross-docking terminal with product perishability considerations

An efficient product distribution is critical for proper supply chain operations. Many supply chains handle perishable products that decay over time. Due to mismanagement of supply chain operations, a significant portion of perishable products is wasted, resulting in substantial monetary losses. Cross-docking terminals (CDTs) have been widely used in cold supply chains for the product distribution but have not received adequate attention in the scientific literature. To improve the efficiency of perishable product distribution, this study introduces for the first time a novel mixed-integer mathematical formulation for the truck scheduling optimization at a cold-chain CDT. The model explicitly captures the decay of perishable products throughout the service of arriving trucks and accounts for the presence of temperature-controlled storage areas that are specifically designated for perishable products. The objective minimizes the total cost incurred during the truck service. Considering the complexity of the proposed model, a customized Evolutionary Algorithm is developed to solve it. The computational performance of the developed algorithm is assessed throughout the numerical experiments based on a detailed comparative analysis against the other metaheuristics. The developed Evolutionary Algorithm is found to be the most promising metaheuristic, considering both solution quality and CPU time perspectives. Furthermore, the proposed algorithm demonstrates an acceptable stability of the solution quality at termination. A set of additional sensitivity analyses are performed in order to draw some significant managerial implications, which would be of potential interest to the supply chain stakeholders that are involved in the distribution of perishable products in cold supply chains.

An Adaptive Polyploid Memetic Algorithm for scheduling trucks at a cross-docking terminal

Many supply chain stakeholders rely on the cross-docking concept, according to which products delivered in specific transportation management units to the cross-docking terminal (CDT) undergo decomposition, sorting based on the end customer preferences, consolidation, and then transported to the final destinations. Scheduling of the inbound and outbound trucks for service at the CDT doors is considered as one of the convoluted decision problems faced by the CDT operators. This study proposes a new Adaptive Polyploid Memetic Algorithm (APMA) for the problem of scheduling CDT trucks that can assist with proper CDT operations planning. APMA directly relies on the polyploidy concept, where copies of the parent chromosomes (i.e., solutions) are stored before performing the crossover operations and producing the offspring chromosomes. The number of chromosome copies is controlled through the adaptive polyploid mechanism based on the objective function improvements achieved and computational time changes. Moreover, a number of problem-specific hybridization techniques are used within the algorithm to facilitate the search process. Computational experiments show that the application of adaptive polyploidy alone may not be sufficient for the considered decision problem. Hybridization techniques that directly consider problem-specific properties are required in order to improve solution quality at convergence. Furthermore, the APMA algorithm developed in this article substantially outperforms some of the well-known state of the art metaheuristics with regards to solution quality and returns truck schedules that have lower total truck service cost.

Consequences of logistics sprawl: Order or chaos? - the case of a parcel service company in Paris metropolitan area

Logistics sprawl is the phenomenon driving warehouses and freight terminals further and further away from city centers, for reasons that are mostly dependent on urban planning, field price and economies of scale. In the past, studies have already described logistics sprawl in Paris Metropolitan area. These studies have concluded that logistic facilities far from Paris city center increased the distance travelled, and by extension, CO2 emissions. This study does not question logistics sprawl in Paris metropolitan area but questions its consequences.This study presents a point of view on the location of cross-docking terminals. One main parcel service carrier was studied through a database strong of 600,000 inputs including pick-ups and deliveries for two months in the Paris metropolitan area. This study is not intended to be representative of all merchandise flows but makes it possible to understand the running of one significant actor. This project aims at determining the optimum terminals location according to two criteria: minimization of the total distance as calculated by the Euclidean distance (as the crow flies) between terminals and points of pick-up/ delivery, and the number of authorized terminals. The number of terminals is modified to study its relationship with the spatial distribution of its clients.Interestingly, we found that optimized locations for this parcel service carrier are located outside of Paris city center. Those locations minimize the total distance to the clients, and thus, are the best places to limit pollution. The reason is that the carrier manages this perimeter through a polycentric organization. Paris Metropolitan area is viewed as several sectors and not as a whole for this carrier. It is therefore unknown how the carrier's performance has evolved over time, but its current organization is close to the optimal situation.

Distribution Network Design for E-Retailing Application: A Model Suggestion for Local Retailer in Izmir

Purpose – The rapid development of technology, acceleration of internet with this development and increase of number of electronic devices that connecting to internet brings important changes in all business applications. The retailing sector, connecting businesses and end consumers, has also changed from classical approach, and consumers started to prefer e-retailing channels versus traditional stores. Therefore, businesses, which have to deliver products to those consumers, are also forced to make critical changes in supply chains. On the other hand, businesses that aim to completely change distribution networks in supply chains adopt a strategy called cross-docking to take the lead over competitors and gain cost advantages. Therefore, in this study, aim is to reveal whether a conventional retailer that does not apply e-retailing can gain by using e-retailing application in coordination with cross-docking strategy. Design/methodology/approach – In application part, it is emphasized that business, which continues retail activities in conventional way, also uses its stores as cross-docking terminals for e-retailing. For this purpose, a mixed integer programming model has been created and it is aimed to have optimal solution for minimizing number of stores and total cost. Findings – In numerical example, it was decided that company which has currently seventeen stores in eleven different regions in Izmir should use nine of these stores as cross docking terminals. Discussion – In numerical example, it was decided that company which has currently seventeen stores in eleven different regions in Izmir should use nine of these stores as cross docking terminals.

Managing loading and discharging operations at cross-docking terminals

A cross-docking terminal is a relevant node within a distribution chain. Actually, at this intermediate logistic platform between suppliers and retailers, incoming flows of possible different commodities are consolidated into single shipments, with respect to the retailers\’ orders, and directly delivered, skipping thus the storage phase. In such a context the synchronization of the inbound and outbound trucks is a necessary condition to guarantee fast and congestion-free transshipment operations. In this paper we propose a Mixed Integer Linear Program and a heuristic algorithm for managing the loading and discharging operations, with the aim of minimizing the completion time of the whole transshipment process.

Truck Scheduling at Cross-Docking Terminals: A Follow-Up State-Of-The-Art Review

Recent trends in the management of supply chains have witnessed an increasing implementation of the cross-docking strategy. The cross-docking strategy, being the one that can potentially improve supply chain operations, has received a lot of attention from researchers in recent years, especially over the last decade. Cross-docking involves the reception of inbound products, deconsolidation, sorting, consolidation, and shipping of the consolidated products to the end customers. The number of research efforts, aiming to study and improve the cross-docking operations, increases every year. While some studies discuss cross-docking as an integral part of a supply chain, other studies focus on the ways of making cross-docking terminals more efficient and propose different operations research techniques for various decision problems at cross-docking terminals. In order to identify the recent cross-docking trends, this study performs a state-of-the-art review with a particular focus on the truck scheduling problem at cross-docking terminals. A comprehensive evaluation of the reviewed studies is conducted, focusing on the major attributes of the cross-docking operations. These attributes include terminal shape considered, doors considered, door service mode considered, preemption, internal transportation mode used, temporary storage capacity, resource capacity, objectives considered, and solution methods adopted. Based on findings from the review of studies, some common issues are outlined and future research directions are proposed.

Truck synchronization at single door cross-docking terminals

We address the problem of synchronizing the loading and discharging operations of trucks at a particular cross-docking center, with one door at both the inbound and outbound sides, aiming at minimizing the makespan of the whole process. We propose a mixed integer linear model and a Lagrangian decomposition scheme. We derive conditions for optimally solving both the Lagrangian relaxation and the dual problems. Based on the theoretical results, we propose a Lagrangian heuristic for computing many feasible solutions and gathering the best one among them. An extensive computational experience validates our Lagrangian heuristic, also in comparison with a state-of-the-art benchmark solver and a heuristic algorithm from the literature.

A Comprehensive Evaluation of Weak and Strong Mutation Mechanisms in Evolutionary Algorithms for Truck Scheduling at Cross-Docking Terminals

Freight transportation is important for the national economy in many countries. An efficient distribution of products within supply chains may lower the associated costs and allow setting competitive prices to increase the number of sales. Many supply chain players use the cross-docking terminals to facilitate the cargo distribution process. An effective scheduling of the arriving trucks at the cross-docking terminals is critical to ensure their timely service. A number of Evolutionary Algorithms have been developed to solve the truck scheduling problem, some of which apply strong mutation for altering solutions throughout the search process, while the rest rely on weak mutation without providing any justification for applying a specific mutation mechanism. This study performs a comprehensive comparative analysis of the strong and weak mutation mechanisms. Furthermore, a novel heuristic algorithm, which accounts for the truck service priority and the truck service order restrictions, is proposed for initializing the chromosomes and population. The truck scheduling problem at a cross-docking terminal is formulated as a mixed integer programming model, minimizing the total weighted truck service cost. An Evolutionary Algorithm is designed to solve the problem. Two categories of the Evolutionary Algorithm, one of which applies strong mutation, while the other one relies on weak mutation, are evaluated based on various performance indicators. Results demonstrate that deployment of weak mutation improves the objective function value at termination on average by 10.8% as compared with strong mutation without affecting the computational time substantially. The analysis also shows that weak mutation yields more diverse population. Moreover, the proposed heuristic for initializing the chromosomes and population outperforms the initialization mechanisms that are commonly used in the literature.

Truck scheduling in cross-docking terminals with fixed outbound departures

At a cross-docking terminal, inbound shipments are directly transshipped across the terminal to designated outbound trucks, so that delays and inventories are kept as low as possible. We consider an operational truck scheduling problem, where a dock door and a start time have to be assigned to each inbound truck. A set of outbound trucks is scheduled beforehand and, therefore, departure times are fixed. If a shipment is not unloaded, transshipped to the outbound gate and loaded onto the designated outbound truck before its departure, we consider the shipments's value as lost profit. The objective is to minimize total lost profit. This paper at hand formalizes the resulting truck scheduling problem. We settle its computational complexity and develop heuristics (namely, decomposition procedures and simulated annealing) in order to tackle the problem. We show the efficiency of these heuristics by means of a computational study. Last but not least, a case study is presented.

Scheduling incoming and outgoing trucks at cross docking terminals to minimize the storage cost

Cross docking terminals allow companies to reduce storage and transportation costs in a supply chain. At these terminals, products of different types from incoming trucks are unloaded, sorted, and loaded to outgoing trucks for delivery. If the designated outgoing truck is not immediately available for some products, they are temporarily stocked in a small storage area available at the terminal.

Scheduling compound trucks in multi-door cross-docking terminals

One of the most important operational management problems in a cross-docking terminal is truck scheduling problem. In this paper, we consider a truck scheduling problem for three types of trucks (inbound-only trucks, outbound-only trucks, and compound trucks) in a multi-door cross-docking terminal. The objective of the problem is to determine the door assignments and the docking sequences of all three types of trucks simultaneously to minimize the makespan. A mathematical model for optimal solution is derived and two meta-heuristics, genetic algorithm and self-evolution algorithm, are proposed. The performance of the meta-heuristic algorithms are evaluated using randomly generated several examples.

A Review on Quantitative Approaches for Dock Door Assignment in Cross-Docking

Cross docking is a relatively new technique in supply chain operations. It offers limited storage time to maximize the efficiency of goods transshipment. Efficient operation of a cross docking system requires an appropriate coordination of inbound and outbound flows, accurate planning and dynamic scheduling. The planning strategies at cross docking terminals, which are receiving growing attention today, are the truck-to-door assignment and destination to door assignment problems. This paper provides a comprehensive literature review of quantitative approaches in dock door assignment problems of cross docking planning. The contributions of this paper are to identify the gap of knowledge in operational levels mainly in dock door assignment and to point out the future research direction in cross docking.

다수의 도어를 갖는 크로스도킹 터미널에서 입고와 출고를 병행하는 트럭일정계획을 위한 유전알고리즘

Cross docking is a logistics management concept in which items delivered to a terminal by inbound trucks are immediately sorted out, routed and loaded into outbound trucks for delivery to customers. Two main advantages by introducing a cross docking terminal are to consolidate multiple smaller shipment into full truck load and remove storage and order picking processes to save up logistics costs related to warehousing and transportation costs. This research considers the scheduling problem of trucks in the cross docking terminals with multi-door in an inbound and outbound dock, respectively. The trucks sequentially deal with the storage process at the one of inbound doors and the shipping process at the one of the outbound doors. A mathematical model for an optimal solution is derived, and genetic algorithms with two different chromosome representations are proposed. To verify performance of the GA algorithms, we compare the solutions of GAs with the optimal solutions and the best solution using randomly generated several examples.

Truck scheduling at zero-inventory cross docking terminals

Handling freight at cross docking terminals constitutes a complex planning task which comprises several executive steps as shipments delivered by inbound trucks are to be unloaded, sorted according to their designated destinations, moved across the dock and finally loaded onto outbound trucks for an immediate delivery elsewhere in the distribution system. To enable an efficient synchronization of inbound and outbound flows, a careful planning of operations, e.g. by computerized scheduling procedures, becomes indispensable. This work treats a special truck scheduling problem arising in the (zero-inventory) cross docks of the food industry, where strict cooling requirements forbid an intermediate storage inside the terminal, so that all products are to be instantaneously loaded onto refrigerated outbound trucks. The problem is formalized such that different operational objectives, i.e. the flow time, processing time and tardiness of outbound trucks, are minimized. To solve the resulting truck scheduling problem suited exact and heuristic solution procedures are presented.

Scheduling inbound and outbound trucks at cross docking terminals

At cross docking terminals, shipments from inbound trucks are unloaded, sorted and moved to dispatch points where they are directly loaded onto outbound trucks for an immediate delivery elsewhere in the distribution system. This warehouse management concept aims at realizing economies in transportation cost by consolidating divergent shipments to full truckloads without requiring excessive inventory at the cross dock. The efficient operation of such a system requires an appropriate coordination of inbound and outbound trucks, e.g. by computerized scheduling procedures.This work introduces a base model for scheduling trucks at cross docking terminals, which relies on a set of simplifying assumptions in order to derive fundamental insights into the underlying problem’s structure, i.e. its complexity, and to develop a building block solution procedure, which might be employed to solve more complex real-world truck scheduling problems.