Optimal Product Allocation for Crossdocking and Warehousing Operations in FMCG Supply Chain Zhengping Li Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, Singapore 638075
[email protected] Cheng Hwee Sim Integrated Decision System Consultancy Pte Ltd., No.1 Jalang Kilang Timor, Singapore 159303
[email protected] Abstract - Many companies search for efficient distribution alternatives, as the lead times for customer order-fulfillment need to be shortened while the costs and risks of warehousing need to be minimized. Crossdocking is an operation strategy that moves items through flow consolidation centers or cross docks without putting them into storage. A distribution center normally is a combination of crossdocking and warehousing facilities. The operator of the center needs to be clear on what products or even how many percent of a type of product should go through by crossdocking. Industry needs guideline and model to support crossdocking/warehousing decision-making and produce alternative plan for allocating products to crossdocking and warehousing operations. This paper presents a systematic procedure and model for evaluating crossdocking distribution in a company. A prototype system based on the approach is discussed and testing analysis is given in the paper. Keyword - Logistics, Supply chain, Crossdocking, Distribution
I. BACKGROUND The traditional warehousing/distribution meets challenges in fulfilling increasing consumer demand. The challenges put pressure primarily on the companies’ warehousing and distribution system. As the number of partners and delivery points grow, the volume of orders decreases. However, as their delivery frequency increases, the time for receiving goods becomes shorter. The prescription relating to the working hours of drivers become stricter and also order lead time becomes even shorter [1]. There is ever increasing pressure to reduce inventories. A trend toward smaller and fewer warehouses will transfer many warehouse operations into crossdocking operations in the 21st century [2]. The implementation of crossdocking operations repositions the focus from warehousing inventory to one of managing inventory through-flow in transit from suppliers to customers. In the fast moving consumer goods (FMCG) crossdocking scenario, retailers order products from suppliers who consolidate orders and send truckloads of product to the crossdock. There, workers transfer products to trailers bound for individual stores, so that outgoing trailers contain products for a single store from many vendors. Transportation costs could be lower because shipments in and out of the crossdock are in truckload quantities. In this process, the warehouses, as crossdocks, are transformed from inventory repositories to
Malcolm Yoke Hean Low School of Computer Engineering, Nanyang Technological University, Singapore 639798
[email protected] Yan Guan Lim Singapore Institute of Manufacturing Technology 71 Nanyang Drive, Singapore 638075
[email protected] points of delivery, consolidation and pickup [3]. Global companies such as Wal Mart [4], UPS [5] have reported implementation of crossdocking. The well-known success of Wal-Mart in crossdocking requires coordinating 2000 dedicated trucks over a large network of warehouses, crossdocks and retail points. Crossdocking operations increase the complexity of material flow control. It could involve a large number of transshipment points and vehicles. This is especially evident when a multitude of suppliers are included in the processes. Not all products are suitable for crossdocking. And even if they are suitable, logistics managers are still skeptical to the idea of not having any safety inventory or crossdocking capacity is not enough for all the suitable products. So there are very few “pure” crossdocking operations. In reality, some blend of cross docking and traditional warehousing occurs [8]. It means both traditional warehousing and crossdocking coexist. Especially in FMCG supply chains, a model combining both crossdocking and traditional warehousing operations is highly feasible and cost effective due to the characteristics of fast moving consumer goods. However, selection of distribution strategy for products depends on a number of factors; e.g. product volume, product value, product life cycle, facility space constraint and etc. Due to the complexities and challenges of crossdocking operations, industry needs approaches for evaluating the potential for crossdocking application. Also, with different cost structures and the limited capacity of crossdocking and warehousing, it is a challenge to produce a plan to allocate products to crossdocking and warehousing operations. Logistic service providers capable of offering crossdocking service are increasingly available, and the developments in IT have also made the management of crossdocking operations easier. Nevertheless, there is still an absence of systematic guidelines on product allocation planning for crossdocking/warehousing operations. In this paper, we first reviewe current research and applications on crossdocking planning and operations. We then propose an approach for allocating products to crossdocking-warehousing operations. A tool developed for crossdocking product allocation planning will also be introduced.
II. LITERATURE REVIEW Research work on crossdocking has focused on areas such as crossdocking system design, layout design, network design, and crossdocking operations scheduling. Rohrer [6] discussed modeling methods and issues as they apply to crossdocking systems. He described how simulation helps to ensure success in cross docking systems design by determining optimal hardware configuration and software control. Apt and Viswanathan [7] addressed a framework for understanding and designing crossdocking systems and discussed techniques that can improve the overall efficiencies of logistics and distribution networks. Napolitano et al. [8] investigated on design crossdocking system, analysis of cost saving and benefits of crossdocking and maintenance of crossdocking systems. Barthold and Gue [9] determined the best shape for a crossdock by analyzing the assignment of receiving and shipping doors. A simulated annealing procedure was used to construct effective layout to reduce labor costs. The staging of products in a crossdock to avoid floor congestion and increase throughput has also been studied together with the effects of different combinations of number of workers in receiving and shipping on throughput [10, 11]. Another important research area for cross-docking is to treat crossdocks as a network of distribution and transshipment points. Donaldson et al. [12] studied a network of crossdocks for the US Postal Service where 148 Area Distribution Centers serve as crossdocks, each receiving, sorting, packing and dispatching mail according to operating schedules. Mail not processed on time must be shipped by air, incurring additional costs and “critical-entry” times, when mail must arrive at the destination center. This must be coordinated with transportation schedules to avoid overshooting specified cut off times. Each distribution center serves as an origin as well as destination node where schedules were driven by mail delivery standards. Ratliff et al. [13] studied a load-driven network, in which deliveries take place when there are sufficient products waiting for transportation. Chen, Guo and Lim [14] studied crossdocking network scheduling where time windows for deliveries and pickups are considered. They also considered crossdock-handling costs which are use to penalize delays. Yu and Egbelu [15] studied the scheduling issue of inbound and outbound trucks in crossdocking systems with temporary storage. They try to find the scheduling sequence for both inbound and outbound trucks to minimize total operation time when a temporary storage buffer to hold items temporarily is located at the shipping stock. Chen and Lee [16] develop polynomial approximation algorithm and branch-and-bound algorithm to minimize the makespan for products going through a crossdocking facility. In strategic and tactical level planning, there is still an absence of systematic approaches that can produce product allocation plan for crossdocking and warehousing operations. Based on the above reviews, despite there being a number of research publications on crossdocking operations, there is
limited published research on the approaches for decisionmaking on product allocation planning for crossdocking and warehousing operations. III. PROBLEM DESCRIPTIONS Companies invest time and money to investigate on the issue of gaining a competitive edge over their rivals especially for FMCG products that have a quick turnover and relatively low cost. The profits made from these products are relatively low. However when they are sold in big volume, the cumulative profit on such products can be significant. To increase their revenue, companies have realized the importance of reducing their distribution cost at the same time meeting the customer demand. The crossdocking-warehousing decision on what and how many products should go for crossdocking could be a complex decision considering product popularity, volume, demand variation and lift cycle etc. It is quite a challenge for a crossdocking manager or operators to make the right decision with these complexities. The objective of this research is to study optimal approaches for allocating products to crossdocking and warehousing operations and develop tools for crossdocking product allocation to assist logistics managers in their product distribution strategies. The issue here is how different products can be allocated to crossdocking and warehousing so that the total operations cost of the facility is minimized with demand fulfilled during a period of time. The following assumptions are applied in this study: • The model is applied to a distribution center which has both crossdocking and warehousing functions, but the facility capacities for crossdocking and warehousing are limited; • Multiple types of products are processed in the facility; • Products are packaged in pallets. One pallet includes one type of product; • A container can take multiple pallets which are with different type of products; 5) Unit product processing costs by warehousing and crossdocking are known. An example of the problem is given below. Considering the following scenario: A retailer R sells 3 products: Product A, Product B and Product C. The demand space required for each product of A, B and C are 75, 150 and 375 respectively. Retailer R’s distribution center has both warehouse and crossdock facilities with limited capacity. The supplied capacities of warehousing and crossdocking are 350 and 150 respectively. Unit product processing costs could be calculated. In this example, we assume that the cost of 1 unit of space through warehouse for products A, B, C are 10, 30 and 50 respectively. The cost of 1 unit of space through crossdock for products A, B, and C are 20, 40 and 50 respectively. The supply of capacity of the facility may not equal to the demand to capacity. We can model the problem generically into a linear programming (LP) problem by expressing the
problem variables in standard form. The problem is formulated as below: Min Z = 10*Xa[W] + 30*Xb[W] + 50*Xc[W] + 20*Xa[C] + 40*Xb[C] + 20*Xc[C] where Z refers to the total cost of distributing products A, B and C through the warehouse and crossdock facility; Xa, Xb and Xc refer the amount of space allocated to products A, B and C, either through warehouse or crossdock. The solution is subject to constraints of capacity, for example, Xa[W] + Xb[W] + Xc[W]
