Risk pooling via unidirectional inventory transshipments in a decentralized supply chain

We study risk pooling via unidirectional lateral transshipments between two locations under local decision-making. Unidirectional transshipments can be applicable when cost structures and/or capabilities differ between locations, and it is also a common practice in dual channel supply chains with online and offline sales channels. We show that such a system cannot be coordinated only with varying transshipment prices. The transshipment receiver orders more and the transshipment giver orders less than the respective optimal centralised order quantities. In order to remove this discrepancy, we suggest horizontal coordinationmechanisms by introducing a leftover subsidy for the location providing the transshipments or a shortage subsidy for the location receiving transshipments as well as a combination of shortage and leftover subsidy. Further, we evaluate the impact of network structure by comparing the equilibrium order quantities and profits under the uni- and bidirectional systems as well as a system without transshipments. Since demand correlation is a critical aspect in risk pooling we provide a detailed numerical study to discuss its impact on our findings

Inventory models with lateral transshipments : a review

Lateral transshipments within an inventory system are stock movements between locations of the same echelon. These transshipments can be conducted periodically at predetermined points in time to proactively redistribute stock, or they can be used reactively as a method of meeting demand which cannot be satised from stock on hand. The elements of an inventory system considered, e.g. size, cost structures and service level denition, all in uence the best method of transshipping. Models of many dierent systems have been considered. This paper provides a literature review which categorizes the research to date on lateral transshipments, so that these dierences can be understood and gaps within the literature can be identied

Supply Chain Coordination under Advance-purchase Discount Contract with Sales Effort and Transshipment

In today’s business environment, a competition is no longer about competing between firms, but between supply chains. Improving supply chain’s performance has become necessary for companies to survive. Supply chain coordination ensures a maximumperformance of a supply chain. This dissertation studies impacts of an advance-purchase contract and supply chain coordination in two different supply chains.We first consider the supply chain with the manufacturer and retailer who can exert sales effort to stipulate demand. We develop the contract that combines the advance-purchase contract and the target rebate contract to coordinate the retailer’s ordering and effort decisions. We analytically show that supply chain coordination is achievable, but profit splitting may not be fully flexible depending on market conditions.We second consider the supply chain with the manufacturer and two retailers who can transship products to satisfy unmet demand as a result of an inventory shortage. We establish a new mechanism that integrates the advance-purchase contract to coordinate the supply chain. The coordination mechanism follows in two steps: it first aligns the objective of the retailer group with the objective of the supply chain, and second aligns the individual objective of each individual retailer with the joint objective of the retailer group. We analytically show that supply chain coordination and arbitrary profit split is achievable.The coordinating contracts lead to Pareto improving situations. The numerical analyses show the performance improvement of the supply chain from the inclusion of the advance-purchase contract. We also conduct the sensitivity analyses to see the impacts of the contract terms on the retailers’ optimal decisions, and the impacts of market conditions on the contracts. The potential future research directions for both studies are also discussed.Industrial Engineering & Managemen

Supply Chain

Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications

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.Peer Reviewe

Transshipment in supply chain networks with perishable items

Supply chain management is an efficient approach to managing the flow of information, goods, and services in fulfillment of customer demand. The implementation of supply chain management significantly affects the cost, benefit level, and quality. Over the past decades, multiple strategies for effective supply chain management have been developed in both academia and industry. One such strategy is named lateral transshipment which allows movement of stock between locations at the same echelon level or even across different levels. Although transshipment has been considered in the literature for a long time, there has been limited studies of transshipment for perishable items, most likely because of the complex structure of perishable inventories. The analysis of perishable-inventory systems has been considered in numerous articles because of its potential application in sectors such as chemicals, food, photography, pharmaceuticals, and blood bank management. Blood services in Australia rely on voluntary, non-remunerated donors to satisfy the demand for blood. Blood services confront ongoing challenges in providing an adequate supply of blood and blood products. One of the powerful tools that could improve the efficiency of the blood supply chain is lateral transshipment. This thesis presents three models that have application in the transshipment of perishable items such as blood. The first model (presented in Chapter 2) outlines the development of a new transshipment policy for perishable items, to enhance supply chain performance. A Poissondistributed customer demand is assumed and the effect of reactive transshipment on expected costs are evaluated. A heuristic solution is developed, using partial differential equations to compute performance measures and cost function. The performance of this model is evaluated through a numerical study. The results indicate that this transshipment policy is effective under lost-sale and backordering scenarios. In addition, the performance of the suggested transshipment policy is compared with the current transshipment policy that is practiced in some Australian hospitals. The results suggest that by setting the optimal threshold, a significant cost saving could be obtained with the same average issuing age of the current policy. The second model (presented in Chapter 3) considers a finite-horizon multi-period inventory system with one main hospital connected to several smaller hospitals. The hospitals face random demand and small hospitals are allowed to transship to the big hospital to mitigate their wastage. The problem is formulated as an infinite-horizon dynamic programming model. The objective of this model is to determine an optimal ordering and transshipment policy that minimizes the total expected cost. An approximate dynamic programming (ADP) model is used to approximate the value function with a linear combination of basis functions, using column generation to cope with the course of dimensionality. The numerical results suggest that considerable cost saving can be achieved by using an ADP model. The third model (presented in Chapter 4) proposes a proactive transshipment policy for a network of hospitals with uncertain demand. At the beginning of each review period, each hospital makes decisions on the quantity to order from a central blood bank and to transship to other hospitals. The problem is formulated as a two-stage stochastic programming model where the Quasi-Monte Carlo (QMC) sampling approach is used to generate scenarios and the optimal number of scenarios is determined by conducting stability tests. The performance of the developed model is evaluated through numerical experiences. The numerical results indicate significant potential cost savings in comparison with the current policy in use and the no-transshipment policy