• 산업공학
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• 제19권1호
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• pp.26-33
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• 2006

Many Firms consider the application of a cross-docking system to reduce inventory and lead-time. However, most studies mainly concentrate on the design of a cross-docking system. This study presents the method that selects the cross-docking center under the existing logistics network. Describing the operation environment to apply the cross-docking system, the selection criteria of the cross-docking center, and the main constraints of transportation planning under the environment of multi-level logistics network, we define the selection problem of the cross-docking center applied to a logistics field. We also define the simulation model that can analyze variously the cross-docking volume and develop the selection methodology of the cross-docking center. The simulation model presents the algorithm and influence factors of the cross-docking system, the decision criteria of the system, policy parameter, and input data. In addition, this study analyzes the effect of increasing the number of simultaneous receiving and shipping docks, and the efficiency of the overnight transportation and cross-docking by evaluating each scenario after simulating the scenarios with the practical data of the logistics field.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.325-328
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• 2003

Fierce competition in today's global markets, the heightened expectation of customers have forced business enterprises to invest in, and focus attentions on, their Supply Chains, Also Cross Docking is an essential part of SC, and integrating Cross Docking with vehicle routing scheduling is needed to smoothly link the physical flow of SC, However, there is no the mathematical model which focuses on Cross Docking with vehicle routing scheduling. Therefore, the integrating model considers Cross Docking and vehicle routing scheduling will be developed in this paper. And the solution based on Tabu algorithm to this model will be provided.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1754-1757
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• 2006

Recently many firms operate a cross-docking center in addition to run a distribution center to reduce logistics costs and maintain or enhance logistics service. However, it is true that many firms just operate their cross-docking centers as they are without any change, in spite of that the location of the cross-docking center should be changed and operated when the location of distribution center is changed and moved. This study presents the method that re-selects the location of the cross-docking center when the existing distribution center is changed. Describing the operation environment to apply the cross-docking system and the selection criteria of the cross-docking center under the environment of changeable logistics network, we define the simulation model which can analyze and select the location of the cross-docking center applied to a logistics field. The simulation model presents experiential algorithm selecting the location with the data of the demand point such as volume, transportation costs, and delivery distance.

• 대한안전경영과학회지
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• 제19권3호
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• pp.129-135
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• 2017

The respective delivering vehicle loaded with the own cargo moves into the respective delivery area. At the base, the delivery points D1 and D2, for example, have the same starting point but the destination is different. The average delivering time of the delivery vehicle is mostly more than 8 hours a day. Therefore, the efficiency of delivery is generally low. In this study, the deliveries will be forwarded from a base station to a delivery point where cross docking will be applied to a single vehicle, and will be distributed from the cross docking point through cross docking. If the distribution is implemented, one vehicle will not have to be operated from the base to the cross docking point. In that case, logistics cost will be reasonably saved by the reduction of transportation cost and labor time. If one vehicle only runs from the base to the cross docking point, each vehicle will be operated in two shifts, and the vehicle operation can be efficiently implemented. This research model is based on the assumption that the 3 types of ratios between the traffic volume of the vehicles starting at the base and the vehicles waiting at the cross docking point are set to the first ratio of 30% to 70%, the second ratio of 50% to 50% and the final ratio of 70% to 30%. As a result of the study, The delivery time in the cross docking point is much higher than that in present on the condition that the cargo volume in the D2 area is more than 50%. Likewise, the delivery time is slightly higher on the condition that the cargo volume is less than 50%. Time is reduced in terms of 50% model like AS-IS model.

• 대한안전경영과학회지
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• 제10권4호
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• pp.199-207
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• 2008

Many logistics enterprises have made efforts to achieve low costly and high efficient logistics network. The cross-docking system can be a good solution for them. However, it requires tight schedule and all-night operation inevitably for realization of ideal cross-docking. These causes the difficulty of the attainment of daily delivery target and the leave of delivery service persons. In this paper, we develop the line-haul and shuttle service compromised cross-docking model in order to solve the problems practically. We apply the storage process with the cross-docking system and the direct cross-docking between line-haul and shuttle services. The simulation model validates the shorter delivery time by the developed model than the present model.

• 대한안전경영과학회지
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• 제8권3호
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• pp.103-114
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• 2006

A cross docking operation involves multiple trucks (known as inbound trucks) that deliver items from suppliers to a distribution center and multiple trucks (known as outbound trucks) that ship items from the distribution center to customers. Based on customer demands, an inbound truck may have its items transferred to multiple outbound trucks. Similarly, an outbound truck can receive its consignments from multiple inbound trucks. A unique characteristic of a cross docking system is the absence or prohibition of long term storage of items at the distribution center. Items delivered to the distribution center from suppliers are shipped to customers as soon as possible without being placed in storage in the distribution center. The objective of this paper is to develop the optimal operational strategy for finding the best truck docking sequence for both inbound and outbound trucks in order to minimize total operation time where a temporary storage area is not available in a cross docking system.

• Industrial Engineering and Management Systems
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• 제14권3호
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• pp.299-311
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• 2015

Nowadays, the distribution centres aim to reduce costs by reducing inventory and timely shipment. Cross docking is a logistics strategy in which products delivered to a distribution centre by inbound trucks are directly unloaded and transferred to outbound trucks with minimum warehouse storage. Moreover, on-time delivery in a distribution network becomes very crucial especially when several distribution centres and customers are involved. Therefore, an efficient truck scheduling is needed to synchronize the delivery throughout the network in order to satisfy all stake-holders. This paper presents a mathematical model of a mixed integer programming for door assignment and truck scheduling in a multiple inbound and outbound doors cross docking problem according to Just-In-Time concept. The objective is to find the schedule of transhipment operations to simultaneously minimize the total earliness and total tardiness of trucks. Then, a multi-objective differential evolution (MODE) is proposed with an encoding scheme and four decoding strategies, called ITSH, ITDD, OTSH and OTDD, to find a Pareto frontier for the multi-door cross docking problems. The performances of MODE are evaluated using 15 generated instances. The numerical experiments demonstrate that the proposed algorithm is capable of finding a set of diverse and high quality non-dominated solutions.

• 대한안전경영과학회지
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• 제4권3호
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• pp.79-93
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• 2002

크로스도킹이란 물류와 분배의 개념으로서 창고나 분배 센터에서 물품이 재고로 남겨짐이 없이 곧바로 하역 창구에서 적재 창구로 이동되어지는 것을 말한다 창고시설 이나 운영 조건이나 운영 전략에 의해서 다양한 크로스도킹 모델이 생성될 수 있다. 본 연구에서 고려되어지는 크로스도킹 모델은 하나의 독립된 하역 창구와 독립된 적재 창구를 가정하고 있다. 또한 하역 트럭에 적재되어 있는 물품이나 적재 트럭에 실려질 물품의 수와 종류는 사전에 알려져 있다는 것을 가정한다. 또한 고려되어진 창고나 분배창구는 단지 하나의 하역 창구와 하나의 적재 창구를 가지고 있다고 가정된다. 본 연구의 목적은 고려되어진 크로스도킹 시스템의 총 운영 시간을 최소화하기 위한 하역 트럭과 적재 트럭의 일정 계획을 찾는데 있다.

• 대한산업공학회지
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• 제37권3호
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• pp.248-257
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• 2011

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.

• 대한안전경영과학회지
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• 제10권2호
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• pp.187-193
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• 2008

Cross docking is a warehouse management concept in which items delivered to a distribution facility by inbound trucks are immediately sorted out and reorganized based on customer demands and are routed and loaded into outbound trucks for delivery to customers without actually being held in inventory in the distribution facility. In this research, the design of distribution facility for cross docking systems was studied. The objective of this research is to find the minimum number of receiving docks and shipping docks, respectively, in order to meet the daily demand of the distribution center. Two solution approaches are employed in modeling and solving the problem The first approach is mathematical modeling and the second approach is a simulation. The logic developed in the simulation model is expected to apply to the real world situation.