Transshipment Policy Research Articles

Dynamic Complexities in a Supply Chain System with Lateral Transshipments

The horizontal interaction between retailers, coupled with replenishment rules and time delays, makes the dynamics in supply chain systems highly complicated. This paper aims to explore the impacts of lateral transshipments on the stability, bullwhip effect, and other performance measurements in the context of a two-tiered supply chain system composed of one supplier and two retailers. In particular, we developed a unified discrete-time state space model to address two different scenarios of placing orders. Analytical stability results are derived, through which we found that inappropriate lateral transshipment policies readily destabilize the supply chain system. Moreover, the lead time of lateral transshipments further complicates the stability problem. Theoretical results are validated through simulation experiments and the influences of system parameters on performance measures are investigated numerically. Numerical simulations show that lateral transshipments help improve the customer service level for both retailers. It is also interesting to observe that the demand of the two retailers can be satisfied even if only one retailer places orders from the upstream supplier.

Optimal lateral transshipment policies for a two location inventory problem with multiple demand classes

We consider an inventory model for spare parts with two stockpoints, providing repairable parts for a critical component of advanced technical systems. As downtime costs for these systems are expensive, ready–for–use spare parts are kept in stock to be able to quickly respond to a breakdown of a system. We allow for lateral transshipments of parts between the stockpoints upon a demand arrival. Each stockpoint faces demands from multiple demand classes. We are interested in the optimal lateral transshipment policy. There are three ways in which a demand can by satisfied: from own stock, via a lateral transshipment, or via an emergency procedure. Using stochastic dynamic programming, we characterize and prove the structure of the optimal policy, that is, the policy for satisfying the demands which minimizes the average operating costs of the system. This optimal policy is a threshold type policy, with state-dependent thresholds at each stockpoint for every demand class. We show a partial ordering in these thresholds in the demand classes. In addition, we derive conditions under which the so-called hold back and complete pooling policies are optimal, two policies that are often assumed in the literature. Furthermore, we study several model extensions which fit in the same modeling framework.

Optimal resource allocation across related channels

In this paper, we consider resource allocation strategies of a limited resource across two related channels in a multi-period setting. We study a stochastic control problem where the objective is to determine the optimal limited resource allocation policy across two related channels and optimal transshipment policy between these two channels. We characterize some structural results of the optimal resource allocation policy and show that it is determined by three monotone curves.

Distribution of Medication Considering Information, Transshipment, and Clustering: Malaria in Malawi

Malaria is a major health concern for many developing countries. Designing strategies for efficient distribution of malaria medications, such as Artemesinin Combination Therapies, is a key challenge in resource constrained countries. This paper develops a solution methodology that integrates strategic‐level and tactical‐level models to better manage pharmaceutical distribution through a three‐tier centralized health system, which is common to sub‐Saharan African countries. At the strategic level, we develop a two‐stage stochastic programming approach to address the problem of demand uncertainty. In the first stage, an initial round of shipments is sent before the malaria season to each local clinic from district hospitals, which receive medications from regional warehouses. After the malaria season begins, a recourse action is triggered to avoid shortages in the form of (i) lateral transshipment or (ii) delayed shipment. The optimal solutions developed by the strategic model identify small clinic clusters possessing exclusive transshipment policies. Therefore, we decompose the problem at the tactical level, solving each clinic cluster independently using a Markov decision process approach to determine optimal periodic transshipment policies. A case study of our proposed distribution system is performed for 290 facilities controlled by the Malawi Ministry of Health. Numerical analysis of Malawi's distribution system indicates that our proposed cluster‐based decomposition method could near optimally reduce shortage incidents. Moreover, such an approach is robust to challenges of developing countries such as slow paper‐based inventory review, uncertain transportation infrastructure, the need for equitable distribution, and seasonal and correlated demand associated with malaria transmission dynamics.

An age-based lateral-transshipment policy for perishable items

Lateral transshipment is an efficient policy designed to improve the performance of a supply chain. Despite the importance of transshipment for perishable items, few studies consider the issue of perishability. Currently, transshipment in some blood supply chains is based on the age profile of units in hospitals. However, decisions such as the age threshold are made empirically and are fixed for all hospitals. In this paper, we propose a new transshipment policy for perishable items based on the age of the oldest item in the system to improve supply-chain performance. The proposed model has applications for transshipping blood units between hospitals. We develop a heuristic solution using partial differential equations to compute performance measures and cost function. The results demonstrate that our transshipment policy is effective under various circumstances such as lost sale and backordering. We also compare the performance of the suggested transshipment policy to the transshipment policy that is currently practiced in some Australian hospitals (which is an aged based proactive transshipment policy with an empirically set threshold). The results demonstrate that by setting the optimal threshold, hospitals could transfuse units with the same average age of the current policy, while reducing their total inventory cost by approximately 61%.

Meta-prediction model for introducing lateral transshipment policies in a retail supply chain network through regression analysis

This study finds a way to alleviate and predict the effects of uncertainty in a retail supply chain network through lateral transshipment policies. The study develops a simulation-based optimisation model using the ARENA and OptQuest optimisation tool, and proposes an improved application of the lateral transshipment policy, in addition to four existing policies, to solve such uncertainty. A series of experiments is performed, varying significant cost parameters to study their effects on the profit of the whole chain. In order to determine the best transshipment policy and predict its financial performance, a proposed meta-prediction model based on regression analysis is used to assist in making decisions on the implementation of different types of transshipment policies under various cost scenarios. The proposed methodology assists in decision making on the selection and management of a lateral transshipment policy for a retail supply chain network in a certain situation under an uncertain environment. [Received 20 March 2016; Revised 8 September 2016; Revised 7 December 2017; Accepted 13 December 2017]

A new transshipment policy in cluster supply chains based on system dynamics

In this paper, the cross-chain inventory emergency supplementary of two single supply chains is investigated to simulate the transshipment of the supply chain network system in the industrial cluster supply chains. We assume that each single supply chain is composed by a manufacturer, a wholesaler and a retailer. Besides, a new transshipment policy based on system dynamics (SD) is proposed in this paper, called the model of the cross-chain inventory transshipment between two enterprises from both the same tier and different tiers. The new proposed model is different from the model of the cross-chain inventory transshipment between two enterprises at the same tier and the model of the cross-chain inventory transshipment between two enterprises at different tiers, which have been researched by previous scholars. Some comparisons are made among the three models. It is proved that the new proposed model can improve the customer satisfaction level (CSL) and lower the total inventory level than the two other models existing currently.

A transshipment policy for dynamic pickup and delivery services with dual objectives

A transshipment policy for dynamic pickup and delivery services with dual objectives

A transshipment policy for dynamic pickup and delivery services with dual objectives

For pickup and delivery service with multiple couriers, collaboration between couriers through hub transshipment has the potential of improving customer waiting time and courier workload. However, transshipment collaboration calls for postponing the delivery of some jobs to the next time period for the benefit of the greater whole. Therefore, new ideas for mitigating the penalty on those postponed jobs should be further investigated. To this end, this paper presents an analysis of a service policy for two categories of jobs, regular and urgent, under two performance measures for a dynamic environment. For this policy, dominance relationships between routing solutions are derived. A routing method is then developed. Numerical results show that the proposed policy and method is practical in constructing an efficient front in the waiting-time and workload performance space. This paper bridges a methodology gap in applying collaborative hub transshipment to dynamic pickup and delivery services. [Received 28 February 2017; Revised 29 January 2018; Accepted 14 May 2018]

Transshipment policies for systems with multiple retailers and two demand classes

Many retailers discriminate among their customers based on their value to the firm. Instead of losing a customer due to this discrimination or lack of inventory, a retailer might prefer to place a transshipment request with other retailers to satisfy the customer’s demand. The system as a whole can benefit from this type of transshipments. In this paper, we study a problem of a centrally controlled system with multiple retailers. Each retailer serves two types of customers: high priority and low priority. Each retailer employs a rationing policy with a rationing level k in the context of a continuous-review (r, Q) inventory replenishment model. The overall policy is referred to as an (r, k, Q) policy. Retailers can transship items from either other retailers or a more expensive central depot. We propose an enumeration-based approximation to find the cost-minimizing policy parameters for the individual retailers and an approximation procedure to solve the combined rationing and transshipment problem. The latter relies on adjusting the demand arrival rates and the unit transshipment costs for both types of customers at all retailers. An extensive numerical study highlights the impact of transshipments on the retailers’ rationing policies. Without transshipment opportunities among each other, retailers set their policy parameters so that the resulting service levels are high for both types of customers. Allowing transshipments results in more aggressive rationing policies, and retailers with aggressive rationing policies benefit from the transshipments the most.

ANALISIS KEBIJAKAN LARANGAN TRANSHIPMENT (ALIH MUAT) TANGKAPAN PERIKANAN TERHADAP KINERJA USAHA PENANGKAPAN IKAN KAPAL LONG LINE (Studi Kasus Pelabuhan Perikanan Samudera Nizam Zachman DKI Jakarta)

This research aims to know and to analyze the impact of transshipment policy on production and business performance of long line vessels, effectiveness of transshipment policy, and constrain factors on the policy implementation. Respondents of this research are 60 long line vessels with criteria above 50 GT. This research method use qualitative and quantitative descriptive. This research show that the implementation of transhipment policy reduce the catching fishery production by 15% and Tuna commodity by 26%. The impact of transhipment policy also reduce the business performance. This results show that sailing trip is decrease. Otherwise, catching tonage, sizing output and earning are decrease. Effectiveness of transhipment policy on the input and process with indicator of performance very good and so do the output. Constrain factors on implementation of transshipment policy are businessman can not fulfill standart product of freshness, otherwise there is regulation of fishery transhipment activities for carrying fishing vessels yet.

Perishable Inventory Sharing in a Two-Location System

Platelets are critical blood products. The management of platelet inventory is particularly challenging due to its perishable nature with a short shelf-life. Motivated by a platelet inventory management problem at a two-location hospital system, we study how the wastage of platelets, and more broadly perishable products, can be reduced through inventory sharing. In particular, we consider a system with two locations and a single product (e.g., a two-hospital system sharing blood products such as platelets). Each location faces a stochastic demand, and products can be transshipped from one location to the other after demand realization. At each location, products are used to meet demand (or shipped out) in a first-in first-out (FIFO) manner. Although the state of such a complex system consists of the inventory levels of different product ages at both locations, interestingly, we show that the direction of transshipment can be determined by simply comparing the age of the oldest products at each location after meeting demand. Based on this and other structural results, we then prove that a myopic transshipment policy is optimal for a two-period lifetime case and serves as a lower bound on the optimal transshipment quantity for longer lifetimes. Because of its competitive performance and simplicity, a variant of our proposed myopic transshipment policy has been implemented by our partner hospital system, which led to an approximately 20% reduction in platelet outdates.

Transshipments of cross-channel returned products

Companies increasingly employ dual-channeling strategies with online and offline channels to reach customers. The combination of high return rates in e-commerce and the possibility for customers to return products ordered online at any offline store may result in unbalanced inventories. Transshipments can be used to deal with these unbalanced inventories. In this paper we study dynamic policies for transshipment of products that are returned cross-channel from online to offline stores. At the end of each period in a finite sales season, cross-channel returned products can be transshipped back to the online store or kept on-hand at the offline store. Optimal transshipment policies are obtained using a Markov decision process. We introduce a well-performing heuristic based on the expected costs during the sales season, with a maximum deviation of 1.59% from the optimal costs in experiments. Furthermore, we show that in all instances our heuristic outperforms static policies in which products are either always or never shipped back to the online store. We observe that dynamic transshipment policies are more effective than static policies in dealing with imbalances in the initial stock. Dynamic transshipment of cross-channel returns seems to open up possibilities for more effective demand fulfillment of dual-channel companies.

Approximate dynamic programming for lateral transshipment problems in multi-location inventory systems

Companies commonly allocate their inventories across multiple locations based on their historical sales rates. However, random fluctuations in customer purchases, such as those caused by weather conditions and other external factors, might cause significant deviations from expected demand, leading to excess stock in some locations and stockouts in others. To fix this mismatch, companies often turn to lateral transshipments, e.g., the movement of stock between locations of the same echelon.In this paper, we examine multi-location inventory systems under periodic review with multiple opportunities for proactive transshipments within one order cycle. If stockouts occur, demand is lost with no opportunity to backorder. The objective of our model is to find an optimal policy that indicates the sources and the destinations of transshipments as well as the number of units, to maximise the profit of the network. We create a dynamic program that can, in principal, be solved to optimality using Bellman’s equation. However, the size of the state and decision spaces makes it impossible to find the optimal policy for real-world sized problem instances. Thereby, we use forward approximate dynamic programming to find a near-optimal transshipment policy.Finally, we conduct an extensive numerical study to gauge the performance of our transshipment policy. For small size instances, we compare our policy to the optimal one. For larger scale instances, we consider other practically oriented heuristics. Our numerical experiments show that our proposed algorithm performs very well compared to state-of-the-art methods in the literature.

Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain

Warehouse capacity constraint has been one obstacle to achieving the channel-wide optimal decision in inventory management. We studied an integrated inventory model consisting of a single vendor and multiple buyers with warehouse capacity sharing via transshipment. We proposed an optimal transshipment policy by developing nonlinear programming models and genetic algorithms as well as obtaining Karush-Kuhn-Tucker points. This inventory policy can significantly reduce the channel-wide cost and the performance is influenced by the consideration of fixed transshipment costs. Sensitivity analyses show that parameters have different impacts on the channel-wide cost and the performances of the algorithms.

Production disruption, compensation, and transshipment policies

Firms can mitigate the effects of production disruptions by compensating customers for delayed delivery and sharing the redundant capacity from other firms through transshipment. In this study, we provide a framework to jointly optimize these two strategies in a dynamic setting, and in particular we examine how a manufacturer under capacity disruption can reduce loss through employing dynamic strategies over a horizon with T periods. We consider a decentralized lateral system with one disrupted manufacturer and one requested manufacturer. In each period during the disruption, both manufacturers decide whether to transship. We characterize the structure of the optimal transshipment prices and compensation policies for both independent and competitive market scenarios. Based on the equilibrium of the game, we propose the optimal dynamic transshipment decision policies. In the computational experiments, we find that the transshipment conditions under the competitive scenario are less strict than those under the independent scenario.

Mathematically calculating the transit time of cargo through a liner shipping network with various trans-shipment policies

ABSTRACTThis paper derives the mathematical expressions for the transit time of cargo through a liner shipping network. Main efforts are devoted to deriving the calculation expressions of the connection time of cargo during trans-shipment. For the forward and many-to-one trans-shipment policies, we conduct a minor correction towards the expressions in existing studies to improve the completeness. Meanwhile, we propose an alternative but more straightforward calculation method for connection time which bypasses the complicated inductive argument in existing studies. Then we introduce two new trans-shipment policies: backward trans-shipment and one-to-many trans-shipment, and mathematically calculate the corresponding connection times. Numerical experiments also deliver some managerial insights into the effectiveness of backward trans-shipment in transit time control.

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 way for reducing drug supply chain cost for a hospital district: A case study

Purpose: This work aims at providing insights to optimise healthcare logistic of the drug management, in order to deal with the healthcare expenditure cut. In this paper the effects of different drug supply chain configurations, on the resulting average stock, service level and Bullwhip effect, of the studied supply chain, is quantitatively assessed. Design/methodology/approach: A case study of an Italian district has been studied, taking into account three echelons: suppliers, central stock, and hospitals. A model of the various supply chain configurations has been created with the use of the simulation. Specifically, 24 supply chain configurations have been examined, stemming from the combination of several supply chain design parameters, namely: transshipment policies (Emergency Lateral Transshipment or Total Inventory Equalization); re-order and inventory management policies (Economic Order Quantity or Economic Order Interval); required service levels (90% or 95%); the number of available vans (one or two). For each configuration, hospital average stock, service level and a “Bullwhip effect” analysis are computed. To know which input variables are statistically significant, a DoE (Design of Experiments) analysis has been executed. Findings: The output of this paper provides useful insights and suggestions to optimize the healthcare logistic and drug supply chain. According to the developed DoE analysis, it can be stated that the introduction of transshipment policies provides important improvement in terms of service and stock levels. To reduce the Bullwhip effect, which results in a service level decreasing, and in a managing stock costs increasing, it is worth to adopt an EOQ re-order policy. Practical implications: This research gives practical recommendations to the studied system, in order to reduce costs and maintain a very satisfactory service level. Originality/value: This paper fulfils an identified need to study which combination of transshipment policies, re-order/inventory management policies and required service levels, can be the best one to reduce costs and maintain a very satisfactory service level, in the specific logistic system.

Managing transshipments in a multi-retailer system with approximate policies

Using the right transshipment policy is important when transshipments are exercised under demand uncertainty. Optimal transshipment policy can be quite complex in a multi-firm system as optimal actions depend on all system variables. Moreover, both how to select requested retailer and how to respond to requests are in question. We introduce simple, close-to-optimal heuristic transshipment policies for multiple retailers. We first show that heuristic policies may perform even better than self-optimal policy, which is explained by Braess’s paradox. Then we test the performances of various heuristics with respect to centrally optimal policy. When retailers can observe others’ inventory levels, more effective transshipments can be made. Otherwise, a random selection performs quite well. We also observe that although always-accept respond policy is quite close to centrally optimal in small systems, the performance of pairwise-optimal holdback levels to respond requests is more clear and consistent for larger systems.