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Crossdocks play an important role in supply chain operations. Due to the need to decrease transportation lead time to coordinate with other supply chain activities such as just-in-time, make-to-order, or merge-in-transit strategies, shortening the total transfer time at crossdocks is increasingly important. In this research, we use real-time information about freight transferring within a crossdock to schedule waiting inbound trailers in order to reduce the time freight spends in a crossdock. We use dynamic simulation models to compare the performance of several strategies. These are first-come, first-served, look-ahead, minimum processing time, and minimum total time policies. We examine these under different trailer arrival headways, crossdock layouts, and destination distributions. Our simulation results show that our time-based algorithms save more time than the first-come, first-served and look-ahead policies. In addition, these algorithms appear to result in higher service reliability and productivity.
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Crossdocking is a type of hub-and-spoke network operation used to distribute goods from suppliers and manufacturers to vendors and retailers. Through consolidation processes, shipments from various suppliers can be rearranged to create full truckload shipments destined to different retailers in order to attain transportation economies. In addition, retailers' average inventory levels and order cycle times are reduced.
The crossdock is the hub of its distribution network. Any delay in its freight handling can hinder the performance of the whole network. Hence, minimizing the time and/or costs incurred when transporting freight from inbound trailers to outbound trailers in the hub is the main challenge of crossdock operations.
In the past, because of the lack of real-time information about incoming and outgoing shipments, a crossdock supervisor could only draw on his or her past experience to assign waiting trailers to receiving doors. Therefore, the efficiency of typical crossdock operations was, by definition, sub-optimal. For example, case studies such as Gue (1999), Bartholdi and Gue (2000), and Brown (2003) report improvements from 7 percent to 23 percent when applying more efficient scheduling methods. Due to the development of technologies, real-time information about the contents, locations, and destinations of shipments in a crossdock is readily available. For example, with advance shipping notices, information about the contents of incoming trailers is known before they arrive; with radio-frequency identification (RFID) tags attached on freight and RFID readers installed at receiving and shipping doors, information about the movement of freight within the crossdock is available any time. In collaborating with a warehouse management system, this real-time information should allow for the development of more efficient operations.
This research uses real-time information to schedule trailer unloading in order to decrease total freight transfer time. Trailer scheduling policies directly impact freight wait time and travel time and thus affect the performance of crossdock operations. Even though trailer scheduling is important, few studies about this topic have been published. To date those studies focus mainly on minimizing travel distance for the worker. From a practical viewpoint, the travel time from a receiving door to a shipping door might take less than five minutes, but the wait time for one unit of freight in an incoming trailer to be unloaded and for the outgoing trailer to be fully loaded and ready to leave might exceed an hour. Therefore, instead of only measuring travel time/distance to assign waiting trailers, taking into account the wait time that a waiting trailer will impose on itself and other freight should have the potential to increase the efficiency of crossdocking.
In the second section of this article we introduce types of crossdocks and related papers about door assignment and trailer scheduling. In the third section, we propose two time-based algorithms that aim at considering processing time or transfer time to assign waiting trailers. To evaluate these algorithms we built detailed simulation models to imitate the transfer of freight under our algorithms and two other scheduling policies: the first-come, first-served (FCFS) and look-ahead policies. We describe the models and data sets in the fourth section. Simulation results are compared in section five. We conclude by discussing the time-saving effects our algorithms can achieve for crossdock and supply chain operations.
LITERATURE REVIEW
Types of Crossdocks
The crossdocking system, like the just-in-time (JIT) system, is designed to reduce inventory and processing costs, and also aims to attain full-truckload transportation economies within shorter order cycle times. Crossdocking attains these benefits by transferring shipments directly from inbound trailers to outbound trailers with no storage in between. Usually, shipments are shipped within twenty-four hours, but sometimes it could be less than one hour (Apte 2000; Gue 2001).
Crossdocks can be classified by the types of freight handled, the timing of information flows, or the types of staging involved. Here we discuss only the staging types. In Bartholdi, Gue, and Kang's (2001) article, crossdocks are categorized into single-stage, two-stage, and free-stage types. In a single-stage crossdock, pallets are put into queues corresponding to their receiving or shipping doors (see Figure la). So the ratio of receiving doors to shipping doors is close to one. Sandal (2005) and Bartholdi, Gue, and Kang (2001) both use the door ratio of one in their staging queuing studies. In a two-stage crossdock, workers put pallets on the first staging lanes corresponding to the receiving doors. Another set of workers sorts them to the second staging lanes corresponding to the shipping doors (see Figure 1b). Accordingly, more time and labor are required than for the single-stage type. Free staging areas are usually used in the less-than-truckload (LTL) trucking industry. The receiving and shipping doors in an LTL crossdock could be on both sides (see Figure 1c). LTL terminals range in size from six to eight doors to more than 200, even more than 500 doors (Gue 1999). The ratio of receiving doors to shipping doors is close to one half (Gue 1999; Taylor and Noble 2004).
Door Assignment and Trailer Scheduling
Because of the quick freight-transferring characteristic of crossdocks, sizable and dense freight handling is ordinary and necessary. With many trailers arriving at a crossdock during the course of operations, dispatchers need to determine how to handle them efficiently to make the best use of the crossdock's capacity. Assigning trailers to unloading doors, arranging receiving/shipping door locations, optimizing the number of workers and the number of facilities, using staging strategies, and coordinating inbound/outbound schedules are all possible ways to improve these operations. In this article, our focus is on how to assign incoming trailers to receiving doors to help reduce total transfer time for freight.
Allocating shipping doors' locations according to their demands is a good way to keep workers' travel distances short. Tsui and Chang (1990) were the first ones to formulate this door assignment problem. In their paper, they minimize the weighted distances between receiving and shipping doors for LTL crossdocks. Solution algorithms have also been proposed by Tsui and Chang (1992) and Bermudez and Cole (2001). However, this door assignment method works only when the number of incoming and outgoing trailers equals the number of doors. To extend this problem, Lim, Ma, and Miao (2006a, 2006b) segregate trailers into groups by specifying their arrival times and departure times to accommodate the number of trailers greater than the capacity of a crossdock. Because of the specification of trailer departure times, in their study penalty costs are incorporated to account for the costs of unfulfilled shipments.
[FIGURE 1 OMITTED]
Arguing that congestion in front of receiving and shipping doors could increase labor costs and delays if solely considering shortest distance, Bartholdi and Gue (2000) identify three types of congestion that can occur in an LTL crossdock (these are interference among forklifts, dragline congestion, and floor space congestion) and minimize the total labor cost, which includes travel and congestion costs. In their model, they use aggregated demand for each destination (shipping door) and average arriving quantities for each incoming trailer to allocate receiving and shipping doors applying their cost function. Their result represents a good crossdock layout in which trailers have similar loads.
The above door assignment algorithms are suitable for tactical planning that is usually updated once a month or every couple of months. At the operational level, when only one receiving door is available, and several trailers are waiting for unloading, we need to find a way to choose a single trailer from a waiting line. This is the trailer scheduling problem explored in this study. Conventionally, the FCFS rule is the way to assign the next trailer to unload. This rule is fair with respect to the wait times of the trailers, but may not be beneficial to the overall operation of crossdocks.
A scheduling idea similar to the minimizing weighted distance criterion is proposed by Gue (1999). His look-ahead scheduling algorithm turns static criteria into rules that are applicable in a dynamic environment: Each incoming trailer is assigned ranks for each shipping door according to the weighted distances of its contents before or when it is in the trailer waiting line. When a receiving door is available, the look-ahead scheduling algorithm will search for the trailer in the trailer waiting line with its first choice for that receiving door. If none exists, it finds the trailer that would have the second lowest weighted distance when assigned to that receiving door. This process continues until an assignment is made. For example, waiting trailers one, two, and three have their first three priorities as (A, D, E), (B, A, C) and (A, C, B), respectively. When receiving door A is available, waiting trailer one will be chosen because receiving door A can give waiting trailer one the lowest weighted travel distance and it arrives at the trailer waiting line prior to waiting trailer three. On the other hand, if receiving door C is available, since no waiting trailers have receiving door C as first priority, the waiting trailer with its second priority for receiving door C (waiting trailer three) will be chosen. This algorithm is convenient to implement as long as the information about the destinations of pallets in incoming trailers is available. Gue claims a 15 to 20 percent saving in labor cost due to travel, compared to the FCFS rule. Brown (2003) also applies the look-ahead rule in her study.
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