Case study on simulation analysis of a logistics network with multiple products by applying lateral transshipments algorithms

Purpose– Are lateral transshipments an effective instrument to ensure the safe and efficient supply of blood? This paper will use the lens of institutional theory to determine how the blood supply chain can benefit from lateral transshipments and what requirements are necessary for their implementation. The paper aims to discuss these issues.Design/methodology/approach– The research design comprises two stages. First, 16 case studies clustered into two case groups were conducted with transfusion laboratories in UK hospitals resulting in the derivation of eight key themes which were tested using a follow-up survey.Findings– The blood supply chain acts under the influence of significant institutional pressures. Coercive pressures result from regulations enforced to ensure the safe supply of blood, normative pressures are imposed by society, demanding wastage is minimized and mimetic pressure from other hospitals fosters efficient supply chain operation. Lateral transshipments offer a powerful organizational tool to allow the blood supply chain to conform to these pressures.Research limitations/implications– This paper offers a novel institutional perspective on a complex supply chain issue where additional external pressures are seen to complicate the context. Due to the special characteristics of the blood supply chain, generalization of the findings to other industries must be done with care.Practical implications– The paper confirms the benefits of lateral transshipments in a perishable product context. Special requirements for the blood supply chain/health care services are identified.Originality/value– The key contributions of this paper are five propositions which offer an institutional theory perspective on the application of lateral transshipment relationships in the blood supply chain.

Service parts inventory control with lateral transshipment and pipeline stockflexibility

In equipment-intensive industries such as truck, electronics, aircraft and dredging vessel manufacturing, service parts are often slow moving items for which, in some cases, the transshipment time is not negligible. However, this aspect is hardly considered in the existing service logistics literature. In this paper, we consider this aspect and propose a customer-oriented service measure which takes into account pipeline stock and lateral transshipment flexibility. We provide an approximation method for optimizing the stock allocation subject to this service measure. Via extensive numerical experiments, we show that our approximation performs very well for both system performance and costs. Moreover, our numerical experiments show that including lateral transshipment and pipeline stock flexibility in inventory decisions is more beneficial than lateral transshipment alone. The magnitude of this effect is higher for high demand rates and high lateral transshipment cost. Results from a case study in the dredging industry confirm our findings. We therefore recommend the introduction of the pipeline stock information such as the track and trace information from freight carriers in existing ERP systems.

For better supply chain management, it is necessary to think about better managing its cost sources. Inventory is considered the most important element of the supply chain that generates the different logistics costs, mainly the inventory holding cost and the transportation cost. One of the most widely used models to jointly solve these two problems is the Inventory Routing Problem (IRP), which will be the focus of this study. The proposed model in this work deals with a two-tier supply network. The first level contains the supplier with a single vehicle to serve a set of customers with a deterministic and periodic demand that are located at the second level. Our work consists in studying the effect of the increase of the replenishment lead time on the different logistic costs. In addition, we introduced the Lateral Transshipment (LT) technique as an option for inventory transfer if it is economical. New mathematical models corresponding to the above-mentioned problems have been developed and solved by an exact method. The obtained results show that the variation of the replenishment lead time leads to an increase of the different logistics costs and that LT can improve the total network cost and balance the customers' inventory level.

An integrated supplier selection and inventory problem with multi-sourcing and lateral transshipments

Since inventory costs account for half of logistics costs, optimal inventory management to minimise total inventory costs remains a sustainable competitive advantage. Lateral transshipment (LT) is evidently a proven strategy to minimise total inventory costs. The additional LT costs are more than compensated by lowering the stock-out costs. Previous LT models have not been applied to perishable products. Our proposed LT model embodies spoilage costs in the total inventory costs function with the other cost components (purchase from a regular supplier, LT, backordering and holding), and optimises the trade-off among these five key cost components. Numerical examples from a supermarket chain case study demonstrate that, as compared against the no or lower spoilage costs scenarios, lower LT costs are required to trigger the decision point for implementing LT in the higher spoilage costs scenario. However, common to both the with and without spoilage costs scenarios, LT is still the preferred strategy to minimise total inventory costs, given the decision rules are satisfied.

We integrate location and inventory decisions in a three-echelon distribution network model with multiple products, capacitated in-house fleet and proactive transshipments between depots. The problem was originally motivated by the real-life case of a leading company in consumers’ household goods. The company offers a wide range of products which are different from demand pattern and shortage viewpoints. One of the product groups has seasonal trend with possibly lost sales during high seasons and backlog in low seasons, while the others lack any seasonal trend and get backlogged if any shortage occurs. A two-step process consisting of a new practical customer classification framework and a new mathematical model is developed. Total profit and customers’ dissatisfaction in the form of a new service-level measure are considered as the objective functions. To study the effects of transportation capacity on the network’s performance, a second scenario with inclusion of third-party transportation resources is presented. Due to unavailability or insufficiency of required objective data about production capacities and demands, they are assumed to be imprecise (i.e. possibilistic). After converting the original fuzzy model to its equivalent crisp formulation, an interactive solution procedure is applied to deal with the trade-off between the conflicting objectives. Useful managerial insights are also derived from the numerical experiments.

The subject of the present monograph is the ‘Creation of Pooling in Inventory and Queueing Models’. This research consists of the study of sharing a scarce resource (such as inventory, server capacity, or production capacity) between multiple customer classes. This is called pooling, where the goal is to achieve cost or waiting time reductions. For the queueing and inventory models studied, both theoretical, scientific insights, are generated, as well as strategies which are applicable in practice. This monograph consists of two parts: pooling and polling. In both research streams, a scarce resource (inventory or server capacity, respectively production capacity) has to be shared between multiple users. In the first part of the thesis, pooling is applied to multi-location inventory models. It is studied how cost reduction can be achieved by the use of stock transfers between local warehouses, so-called lateral transshipments. In this way, stock is pooled between the warehouses. The setting is motivated by a spare parts inventory network, where critical components of technically advanced machines are kept on stock, to reduce down time durations. We create insights into the question when lateral transshipments lead to cost reductions, by studying several models. Firstly, a system with two stock points is studied, for which we completely characterize the structure of the optimal policy, using dynamic programming. For this, we formulate the model as a Markov decision process. We also derived conditions under which simple, easy to implement, policies are always optimal, such as a hold back policy and a complete pooling policy. Furthermore, we identified the parameter settings under which cost savings can be achieved. Secondly, we characterize the optimal policy structure for a multi-location model where only one stock point issues lateral transshipments, a so-called quick response warehouse. Thirdly, we apply the insights generated to the general multi-location model with lateral transshipments. We propose the use of a hold back policy, and construct a new approximation algorithm for deriving the performance characteristics. It is based on the use of interrupted Poisson processes. The algorithm is shown to be very accurate, and can be used for the optimization of the hold back levels, the parameters of this class of policies. Also, we study related inventory models, where a single stock point servers multiple customers classes. Furthermore, the pooling of server capacity is studied. For a two queue model where the head-of-line processor sharing discipline is applied, we derive the optimal control policy for dividing the servers attention, as well as for accepting customers. Also, a server farm with an infinite number of servers is studied, where servers can be turned off after a service completion in order to save costs. We characterize the optimal policy for this model. In the second part of the thesis polling models are studied, which are queueing systems where multiple queues are served by a single server. An application is the production of multiple types of products on a single machine. In this way, the production capacity is pooled between the product types. For the classical polling model, we derive a closedform approximation for the mean waiting time at each of the queues. The approximation is based on the interpolation of light and heavy traffic results. Also, we study a system with so-called smart customers, where the arrival rate at a queue depends on the position of the server. Finally, we invent two new service disciplines (the gated/exhaustive and the ??-gated discipline) for polling models, designed to yield ’fairness and efficiency’ in the mean waiting times. That is, they result in almost equal mean waiting times at each of the queues, without increasing the weighted sum of the mean waiting times too much.

Contributions to behavioural freight transport modelling

This article aims to provide a description of fundamental elements of discrete event simulation (DES), the process and the values of applying DES in assisting healthcare design and planning decision-making. More importantly, it explores how new technology such as electronic medical records, real-time location services (RTLS), and other simulation methods such as space syntax analysis (SSA) can facilitate and complement DES. Healthcare administrators increasingly recognize DES as an effective tool for allocating resources and process improvement. However, limited studies have described specifically how DES can facilitate healthcare design. Three case studies were provided to illustrate the value of DES in supporting healthcare design. The first case study used DES to validate a surgical suite design for shorter surgeon walking distance. The second case study used DES to facilitate capacity planning in a clinic through testing the utilization of exam rooms upon various growth scenario. The detailed process data for the current clinic were captured through RTLS tracking. The third case study applied DES in an emergency department for both site selection in master planning and capacity test at various growth scenarios with seasonal volume swing. In addition, SSA was conducted to evaluate the impacts of design on visual surveillance, team communication, and co-awareness. It is recognized that the DES analysis is an effective tool to address the process aspects of healthcare environments and should be combined with post-occupancy evaluation and SSA to address behavioral aspects of operations to provide more solid evidence for future design.

Itemized platelet supply chain with lateral transshipment under uncertainty evaluating inappropriate output in laboratories

Manufacturers and wholesalers are increasingly cost conscious in response to today’s hyper-competitive environment. Lateral transshipment (LT) has been proposed as a viable solution to drive total inventory costs down whilst increasing customer service level. Our study proposes five LT decision rules with a case-based roadmap to guide professional inventory management. Results of this large fast moving consumer goods case study company demonstrate superior inventory management performance with implementing a combined reactive and proactive LT strategy to determine whether to transship emergency stock from other warehouse or to backorder from suppliers, size of transshipment, favorite wholesaler, preferred supplier, and extra quantity for preventive LT, which are the key LT decision points among the professional supply chain management practitioners.

Healthcare providers have to keep high availability for critical medical items that are important to save lives, even if these items have low demand rates. However, keeping high availability can result in high expiry of slow-moving medical items because of their finite lifetimes. Lateral transshipment between inventory locations has been reported to reduce expiry of blood products, which are fast-moving. This paper extends lateral transshipment to slow-moving critical items in a medical system to reduce expiry and proposes a decision rule. Transshipment may take place when demand happens at a location or when a unit expires. The proposed decision rule takes the myopic-best action at each decision epoch by assuming no transshipments in the future. The rule is iteratively applied at all decision epochs to realize long-term savings. Simulation results demonstrate significant cost savings by the lateral transshipment based on the proposed decision rule. The decision rule works well compared to the upper-bound percentage of total savings. The savings are more considerable when the difference of demand rates between locations is large and the lifetime of the medical item is not too long or too short. The savings could be more significant when the number of locations increases but is bounded. Furthermore, simulation results on an example of Fomepizole demonstrate about 9.5% cost savings realized by lateral transshipment based on the proposed decision rule.

Service differentiation through selective lateral transshipments

Inventory management in blood supply chain considering fuzzy supply/demand uncertainties and lateral transshipment