Preventive Transshipment Research Articles

Data-driven ordering and transshipment decisions for online retailers and logistics service providers

Emerging advanced technologies enable logistics service providers (LSPs) to offer supply chain services, such as inventory management, rather than only shipping services. In the traditional retailer-led system, the retailer makes the ordering and transshipment decisions and outsources shipping to the LSP, but this paper studies an LSP-led preventive transshipment system where the LSP is the decision-maker, providing the optimal ordering and transshipment policy solution to the online retailer. An optimal two-threshold transshipment policy is proposed for the LSP-led system. The LSP has lower operational cost for transshipment than the retailer, so one may expect that the LSP can bear more risk of mismatch between the transshipment and uncertain demand, leading the LSP to be more aggressive in transshipment. Interestingly, the analysis reveals that the transshipment quantity chosen by the LSP is not necessarily high. The LSP will transfer less inventory between distribution centers than the retailer if the delivery cost or transshipment cost of the LSP, or the lost sale cost, holding fee, or selling price of the retailer are high. Based on real industrial data, the evaluation result shows that preventive transshipment in the LSP-led system can bring an average increase of 40.33% (even 93.31% for products with high demand uncertainty in the first selling period) in the total profit of the retailer and the LSP over the non-transshipment scenario. Importantly, even if the transshipment cost is the same for both the retailer and LSP, using the optimal policy decided by the LSP rather than the retailer will generate a profit improvement of 6.37%.

Hybrid Transshipment Policy and Ordering Model for Multiple Periods with Customer Switching Behaviour

The interaction of a hybrid transshipment policy and customer switching behaviour will exacerbate the complexity of the structure of a hybrid transshipment policy. To cope with this problem, a discrete-time dynamic programming model framework with customer switching behaviour is developed. Based on this framework, we demonstrate that the retailer can obtain more profits with a hybrid transshipment than without one. Next, the existence of a reactive and preventive transshipment policy is shown, respectively. We further analyse the structural property of the holdback policy of reactive transshipment and give the threshold of customer switching rate when always rejecting the request. Meanwhile, a dominant preventive transshipment policy is formulated by which the retailer can control the inventory regardless of the influence of the preventive transshipment policy of the other as long as the inventory is observed by developing an easy-to-implement optimal hybrid transshipment strategy. In addition, the existence of an ordering Nash equilibrium of two retailers is proven. Then, we also illustrate the existence of a transshipment area and analyse the impact of the transshipment cost and switching rate on ordering, the hybrid transshipment policy, and profit by using numerical examples. Finally, we find that the retailer is more willing to adjust inventory by ordering when there is a lower transshipment price and adjust inventory by hybrid transshipment when there is a higher transshipment price.

Coordination in a Single‐Supplier, Multi‐Retailer Distribution System: Supplier‐Facilitated Transshipments

We consider supplier‐facilitated transshipments for achieving supply chain coordination in a single supplier, multi‐retailer distribution system with non‐cooperative retailers. The previous transshipment literature has focused on coordination through retailer‐negotiated transshipments and thus does not consider the supplier's decision‐making. In contrast, in this study, we assume the supplier is an active participant in the system and we seek to understand how the supplier can facilitate the implementation of coordinating transshipments. We study a two‐period model with wholesale orders at the start of the first period and preventive transshipments performed at the start of the second period. Inspired by a supplier‐facilitated transshipment scheme observed in practice, we assume the supplier implements transshipments through a bi‐directional adjustment contract. Under this contract, each retailer can either buy additional inventory from, or sell back excess inventory to, the supplier. We show that coordination can be achieved through carefully designed contracts with state‐dependent adjustment prices and a wholesale price menu. We demonstrate that the supplier's role in facilitating coordinating transshipments is critical. In addition, we use our understanding of the coordinating contract form to derive some simpler and easier‐to‐implement heuristic contracts. We use a numerical study to demonstrate the value, to the supplier, of using the coordinating adjustment and wholesale prices, and to evaluate the heuristics’ performance.

An Application of SLA in Small Business Sectors with Multi Item Inventory Management.

Lateral transshipment plays an important role in inventory management. As the extension the service level adjustment (SLA) which combines preventive lateral transshipment with emergency lateral transshipment, increase the system performance level and decrease the total cost of the system in small business sector. At finally we give a numerical study of multi item small business sector, we examine SLA will be more effective in multi item small business sectors.

Preventive transshipment decisions in a multi-location inventory system with dynamic approach

This paper addresses the preventive transshipment problem in a multi-location inventory system. Decisions are made before demands are observed to prevent future stock out. Both lateral transshipments (LT) and emergency orders (EO) are available in this system. The objective is to figure out the timing and quantity of preventive transshipment decisions. A Markov decision process is formulated to describe the problem. First a decomposition method is used to divide the multi-location problem into different pairs of two-location problems. Then a sorting heuristics combined with backward dynamic programming (BDP) approach and approximate dynamic programming (ADP) approach is developed to solve this problem. Extensive numerical examples are used to demonstrate the effectiveness of this method. Results show that demand distribution at the retailer affects the way transshipment performs. In addition, product’s perishability has obvious effects on transshipment decisions.

Ordering and pricing model of retailers’ preventive transshipment dominated by manufacturer with conditional return

Retailers often fail to implement the transshipment policy due to lack of the trust or information asymmetry among them in the process of transshipment, especially in the case that return becomes a norm. Therefore, we develop a framework about the preventive transshipment which is dominated by the manufacturer between two independent retailers to cope with the mismatch between demand and inventory. In this research, a two-period ordering and pricing model about the preventive transshipment with conditional return is formulated. To simplify the implementation of preventive transshipment, a dominant preventive transshipment policy is recommended at the beginning of the second period. So, one retailer may adjust the inventory without considering the impact of the other retailer’s inventory quantity and the transshipment strategy. To analyze the mutual effect between two retailers, the existence and uniqueness of the ordering Nash Equilibrium and the optimal pricing policy is identified and analyzed. Furthermore, we obtain the relationship between the ordering quantity and transshipment price. Finally, a numerical analysis is carried out to examine the sensitivity of the transshipment price, wholesale price, ordering quantity, profit of the retailer and manufacture to the return rate.

A multi-agent system model for supply chains with lateral preventive transshipments: Application in a multi-national automotive supply chain

In this study, a multi-agent system model is developed to observe the effects of ordering parameters on a supply chain with lateral preventive transshipments. The proposed model involves ordering and premium freight bidding processes of the agents. The model is implemented to a multi-national supply chain considering both supply and demand side uncertainties. Effects of safety stock and supplier flexibility levels on performance are examined by simulation from both agent and system-wide perspective. The results reveal the viability of the proposed model.

Inventory distribution problem via stochastic programming

Previous research on inventory distributions between local warehouses or retailers (bases) has focused separately on either of two types of stock transshipment policies: preventive lateral transshipments or emergency lateral transshipments. Each of these has its advantages and disadvantages, and combining these policies may well enable merchandisers to achieve higher service levels. Thus, the combined use of these policies is the focus of the present study. A stochastic programming problem is formulated with demand as a stochastic variable, and the policy of using both preventive and emergency lateral transshipment is examined for its effectiveness while solution methods are examined for their efficiency.

An innovation approach for achieving cost optimization in supply chain management

This paper presents a joint optimization of the supply chain network in which supplier selection, lateral transshipment, and vehicle routing are involved. Separate consideration of these decisions involved probably offers only poor-quality local optimal solutions. The contribution of this paper is to study the cost minimization of the supply chain network involving the three decisions simultaneously, using both vertical and preventive lateral transshipment, and considering both single objective and multi-objective approach with the following objectives: a minimize the total ordering cost incurred by the wholesaler, b maximize the amount of savings on the different products, and c find the best sequence for delivering various kinds of products to different retailers. A stochastic search technique called fuzzy logic guided genetic algorithms FLGA is proposed to solve the problems. In order to demonstrate the effectiveness of the FLGA, several search methods are compared with the FLGA through simulations in the single objective approach. In the multi-objective approach, two multi-objective evolutionary algorithms entitled Nondominated Sorting Genetic Algorithms 2 NSGA2 and Strength Pareto Evolutionary Algorithm 2 SPEA2 are adopted for comparison with the FLGA. Results show that the FLGA outperforms others in all three considered scenarios for both single objective and multi-objective approaches.

Coordinating preventive lateral transshipment between two locations

We analyze preventive transshipment between two locations in anticipation of the mismatch between demands and inventories, and the effects of the preventive transshipment on ordering quantities. The time horizon for preventive transshipment includes two stages: the ordering stage and the shipping stage. At the ordering stage, the two locations order products from their supplier. During the replenishment lead-time, some demand signals (e.g., the realized demand for a complementary product) may be observed. Therefore, the locations may update their demand distributions and preventively transship to each other at the shipping stage. When the two locations make their ordering and transshipping decisions individually to maximize their own profits, there are incentive problems that prevent coordination. These problems arise even between the locations that pay each other for transshipped units. We examine two commonly used linear transfer price contracts: the ex ante transfer price contract and the ex post transfer price contract. However, neither of these contracts coordinates the transshipment quantities between the two locations. We then present a bidirectional revenue sharing contract that can coordinate the transshipment quantities. We find the conditions under which this proposed contract coordinates the ordering quantities. Finally, we investigate how the transportation cost and the amount of information updating affect the ordering quantities with the coordinating bidirectional revenue sharing contract.

Inventory sharing under decentralized preventive transshipments

AbstractWe consider preventive transshipments between two stores in a decentralized system with two demand subperiods. Replenishment orders are made before the first subperiod, and the stores may make transshipments to one another between the subperiods. We prove that the transshipment decision has a dominant strategy, called a control‐band conserving transfer policy, under which each store chooses a quantity to transship in or out that will keep its second‐subperiod starting inventory level within a range called a control band. We prove that the optimal replenishment policy is a threshold policy in which the threshold depends on the capacity level at the other store. Finally, we prove that there does not exist a transfer price that coordinates the decentralized supply chain. Our research also explains many of the differences between preventive and emergency transshipments, including differences in the optimal transfer policies and the existence or nonexistence of transfer prices that coordinate the system. © 2010 Wiley Periodicals, Inc. Naval Research Logistics, 2010

Inventory Sharing Under Decentralized Preventive Transshipments

We consider preventive transshipments between two stores in a decentralized system with two demand subperiods. Replenishment orders are made before the first subperiod, and the stores may make transshipments to one another between the subperiods. We prove that the transshipment decision has a dominant strategy, called a control-band conserving transfer policy, under which each store chooses a quantity to transship in or out that will keep its second-subperiod starting inventory level within a range called a control band. We prove that the optimal replenishment policy is a modified base-stock policy in which the order-up-to level depends on the initial inventory and capacity level at the other store. Finally, we prove that there does not exist a transfer price that coordinates the decentralized supply chain. Our research also explains many of the differences between preventive and lateral transshipments, including differences in the optimal transfer policies and the existence or nonexistence of transfer prices that coordinate the system.