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Cross-docking is a supply chain distribution and logistics strategy for which less-than-truckload shipments are consolidated into full-truckload shipments. Goods are stored up to a maximum of 24 hours in a cross-docking terminal. In this chapter, we build on the literature review by Ladier and Alpan (2016), who reviewed cross-docking research and conducted interviews with cross-docking managers to find research gaps and provide recommendations for future research. We conduct a systematic literature review, following the framework by Ladier and Alpan (2016), on cross-docking literature from 2015 up to 2020. We focus on papers that consider the intersection of research and industry, e.g., case studies or studies presenting real-world data. We investigate whether the research has changed according to the recommendations of Ladier and Alpan (2016). Additionally, we examine the adoption of Industry 4.0 practices in cross-docking research, e.g., related to features of the physical internet, the Internet of Things and cyber-physical systems in cross-docking methodologies or case studies. We conclude that only small adaptations have been done based on the recommendations of Ladier and Alpan (2016), but we see growing attention for Industry 4.0 concepts in cross-docking, especially for physical internet hubs.

The 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.

In 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.

The 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.

There 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.

In 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.

The purpose of this paper is to investigate the costs/benefits of implementing the cross-docking strategy in a retail supply chain context using a cost model. In particular, the effects of using different typologies of cross-docking compared to traditional warehousing are investigated, taking into consideration an actual case study of a fast-moving consumer goods (FMCG) company and a major French retailer.

The research is based on a case study of an FMCG company and a major French retailer. The case study is used to develop a cost model and to identify the main cost parameters impacted by implementing the cross-docking strategy. Based on the cost model, a comparison of the main cost factors characterizing four different configurations is made. The configurations studied are, the traditional warehousing strategy (AS-IS configuration, the reference configuration for comparison), where both retailers and suppliers keep inventory in their warehouses; the cross-docking pick-by-line strategy, where inventory is removed from the retailer warehouse and the allocation and sorting are performed at the retailer distribution centre (DC) level (TO-BE1 configuration); the cross-docking pick-by-store strategy, where the allocation and sorting are done at the supplier DC level (TO-BE2 configuration); and finally a combination of cross-docking pick-by-line strategy and traditional warehousing strategy (TO-BE3 configuration).

The case study provides three main observations. First, compared to traditional warehousing, cross-docking with sorting and allocation done at the supplier level increases the entire supply chain cost by 5.3 per cent. Second, cross-docking with allocation and sorting of the products done at the retailer level is more economical than traditional warehousing: a 1 per cent reduction of the cost. Third, combining cross-docking and traditional warehousing reduces the supply chain cost by 6.4 per cent.

A quantitative case study may not be highly generalisable; however, the findings form a foundation for further understanding of the reconfiguration of a retail supply chain.

This paper fills a gap by proposing a cost analysis based on a real case study and by investigating the costs and benefits of implementing different configurations in the retail supply chain context. Furthermore, the cost model may be used to help managers choose the right distribution strategy for their supply chain.

An important phenomenon often observed in supply chain, known as the bullwhip effect, implies that demand variability increases as we move up in the supply chain. On the other hand, the cross-docking is a distribution strategy that eliminates the inventory holding function of the retailer distribution center, where this latter functions as a transfer point rather than a storage point. The purpose of this paper is to analyze the impact of cross-docking strategy compared to traditional warehousing on the bullwhip effect.

The authors quantify this effect in a three-echelon supply chain consisting of stores, retailer and supplier. They assume that each participant adopts an order up to level policy with an exponential smoothing forecasting scheme. This paper demonstrates mathematically the lower bound of the bullwhip effect reduction in the cross-docking strategy compared to traditional warehousing.

By simulation, this paper demonstrates that cross-docking reduces the bullwhip effect upstream the chain. This reduction depends on the lead-times, the review periods and the smoothing factor.

A mathematical demonstration cannot be highly generalizable, and this paper should be extended to an empirical investigation where real data can be incorporated in the model. However, the findings of this paper form a foundation for further understanding of the cross-docking strategy and its impact on the bullwhip effect.

This paper fills a gap by proposing a mathematical demonstration and a simulation, to investigate the benefits of implementing cross-docking strategy on the bullwhip effect. This impact has not been studied in the literature.

The technique of cross-docking is attractive to organisations because of the lower warehousing and transportation (consolidated shipments) costs. This concept is based on the fast movement of products. Accordingly, cross-docking operations should be monitored carefully and accurately. Several factors in cross-docking operations can be impacted by uncertain sources that can lead to inaccuracy and inefficiency of this process. Although many papers have been published on different aspects of cross-docking, there is a need for a comprehensive review to investigate the sources of uncertainties in cross-docking. Therefore, the purpose of this paper is to analyse and categorise sources of uncertainty in cross-docking operations. A systematic review has been undertaken to analyse methods and techniques used in cross-docking research.

A systematic review has been undertaken to analyse methods and techniques used in cross-docking research.

The findings show that existing research has limitations on the applicability of the models developed to solve problems due to unrealistic or impractical assumption. Further research directions have been discussed to fill the gaps identified in the literature review.

There has been an increasing number of papers about cross-docking since 2010, among which three are literature reviews on cross-docking from 2013 to 2016. There is an absence of study in the current literature to critically review and identify the sources of uncertainty related to cross-docking operations. Without the proper identification and discussion of these uncertainties, the optimisation models developed to improve cross-docking operations may be inherently impractical and unrealistic.

Collaborative Logistics (CL) and merging operations are crucial strategies for reducing costs and improving service in transportation companies. This study proposes a model for optimizing efficiency in supply chain networks through inbound and outbound Collaborative Logistics implementation among the carriers in centralized, coordinated networks with cross-docking.

A mixed-integer non-linear programming model is developed to determine the optimal truck-goods assignment while gaining economies of scale through mixing multiple less-than-truckload (LTL) products with different weight-to-volume ratios. Unlike the previous studies that have considered Collaborative Logistics from the cost and profit-sharing perspective, the proposed model seeks to determine an appropriate form of Collaborative Logistics in the VRP.

This article shows that in a three-echelon supply chain consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. This approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of collaborative logistics among the carriers was discussed. In a three-echelon SC consisting of a set of suppliers, a set of customers and a cross-docking terminal, partial collaboration among the inbound carriers and outbound carriers outperforms no/complete collaboration. Using a combination of experimental analysis and optimization process, it was recommended that managers be cautious that too much (full or complete) or no collaboration can result in SC performance deterioration.

The suggested approach enhances the supply chain efficiency by minimizing the total transportation costs, the total transportation miles and the total number of trucks and maximizing fleet utilization. While addressing the four points, the role of Collaborative Logistics among the carriers was discussed.

The cost of pharmaceutical supply chain due to drug waste is one of the current major issues in health care. Drug waste associated with intravenous (IV) fluid form of medication is one of the crucial issues for many pharmacies. The purpose of this paper is to apply a cross-docking model to minimize the IV delivery lead time to reduce drug waste by scheduling staff in a local hospital’s inpatient pharmacy.

A mixed integer linear programming model is applied to the IV delivery system of a hospital. The parameters are selected based on the observations made in the inpatient pharmacy.

The result implies that cross-docking approach can be effectively applied to IV delivery system. In fact, the cross-docking optimization model employed in this case study reduces the IV delivery completion time of the inpatient pharmacy by 41 percent.

The scope of this research is limited to the activities performed after IV preparation.

The application of cross-docking system in staff scheduling will be beneficial for health care organizations that aim to minimize medication waste.

The prime value of this study lies in the introduction of a cross-docking concept in an internal hospital ordering process. Cross-docking models are widely used in general supply chain systems; however, their application for specific activities inside hospitals is the novelty of this study, which can fill the research gap in terms of drug waste management within the inpatient pharmacy.

This paper aims to develop a multi-objective problem for scheduling the operations of trucks entering and exiting cross-docks where the number of unloaded or loaded products by trucks is fuzzy logistic. The first objective function minimizes the maximum time to receive the products. The second objective function minimizes the emission cost of trucks. Finally, the third objective function minimizes the number of trucks assigned to the entrance and exit doors.

Two steps are implemented to validate and modify the proposed model. In the first step, two random numerical examples in small dimensions were solved by GAMS software with min-max objective function as well as genetic algorithms (GA) and particle swarm optimization. In the second step, due to the increasing dimensions of the problem and computational complexity, the problem in question is part of the NP-Hard problem, and therefore multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment.

Therefore, non-dominated sorting genetic algorithm (NSGA-II) and non-dominated ranking genetic algorithm (NRGA) are used to solve 30 random problems in high dimensions. Then, the algorithms were ranked using the TOPSIS method for each problem according to the results obtained from the evaluation criteria. The analysis of the results confirms the applicability of the proposed model and solution methods.

This paper proposes mathematical model of truck scheduling for a real problem, including cross-docks that play an essential role in supply chains, as they could reduce order delivery time, inventory holding costs and shipping costs. To solve the proposed multi-objective mathematical model, as the problem is NP-hard, multi-objective meta-heuristic algorithms are used along with validation and parameter adjustment. Therefore, NSGA-II and NRGA are used to solve 30 random problems in high dimensions.

Exel Logistics’ experience in a number of industry sectors, product profiles, operational techniques and technology suggests that the outputs of cross‐docking can appear magical, even though they result from fairly standard operational inputs. Explains the origins of cross‐docking and explores the operational aspects of switching from a traditional stockholding supply chain system to a cross‐docking system, using a case study from the motor industry. States that key benefits resulting from the adoption of cross‐docking techniques relate to improvements in service levels, inventory levels, stock returns and unit costs.

This paper presents a case study of Renault Samsung Motors (RSM) that recently encounters dynamic changes unveiling various opportunities and challenges due to increasing complexity of the supply network with growing sales volume, diversifying models, and intensifying global competition. Such competitive environment puts constant pressure on the logistics operations to reduce supply costs and lead time, but the RSM has not been paying much attention to aligning interests of supply chain partners. In 2007, RSM’s effort to build partnership with new 3PLs turned abortive due to their unexpected default on the contract throwing RSM into confusion and disruptions. In this study, the problem was investigated by examining route planning process and incentive scheme of 3PL, and an optimization model was constructed to evaluate the performance of existing 3PL operation. The results indicate that transportation cost can be reduced by relocating consolidation centers, utilizing regional terminal and redesigning routing sequence. However, the research found that the key to successful implementation of the optimized solutions is in designing effective incentive system that induces partners to participate in continuous improvement initiatives.