Browsing by Subject "Inventory management"

Now showing 1 - 14 of 14

Open Access
Application of AHP to multicriteria inventory classification
(1993) Güvenir, Nuray
In this thesis, a new method based on the application of Analytic Hierarchy Process (AHP) to ABC inventory classification is investigated. The traditional ABC classification method utilizes only the unit price and the annual usage of inventory items. However, in some cases, the classification done using only these two criteria turns out to be insufficient. The method described in this thesis enables the integration of several criteria that can be organized in a hierarchy into ABC classification. The method can be summarized as follows: A matrix is constructed by the pairwise comparison of criteria on the highest level. The elements of the eigen vector of this matrix represent the weights (priorities) of the criteria. If a criterion has subcriteria in the hierarchy, the weights computed in the similar manner for the subcriteria are multiplied by the weight of the criterion and inserted in its place. Repetition of these steps for aU levels of the hierarchy, the weight of all criteria are determined. Using the criteria weights determined by the AHP technique, the weighted score of each inventory item is computed. The items sorted by that weighted score are grouped in three classes: A, B, and C, as in the classical ABC classification. This new method is applied to the classification of inventory items used in rock excavation jobs done using blasting by a construction company. The same inventory is also classified according to the classical ABC technique, and the results are compared.
Open Access
Demand uncertainty and inventory turnover performance: an empirical analysis of the US retail industry
(Emerald Publishing, 2016) Hançerlioğulları, G.; Şen, A.; Aktunç, E. A.
Purpose – The purpose of this paper is to investigate the impact of demand uncertainty on inventory turnover performance through empirical modeling. In particular the authors use the inaccuracy of quarterly sales forecasts as a proxy for demand uncertainty and study its impact on firm-level inventory turnover ratios. Design/methodology/approach – The authors use regression analysis to study the effect of various measures on inventory performance. The authors use a sample financial data for 304 publicly listed US retail firms for the 25-year period from 1985 to 2009. Findings – Controlling for the effects of retail segments and year, it is found that inventory turnover is negatively correlated with mean absolute percentage error of quarterly sales forecasts and gross margin and positively correlated with capital intensity and sales surprise. These four variables explain 73.7 percent of the variation across firms and over time and 93.4 percent of the within-firm variation in the data. Practical implications – In addition to conducting an empirical investigation for the sources of variation in a major operational metric, the results in this study can also be used to benchmark a retailer’s inventory performance against its competitors. Originality/value – The authors develop a new proxy to measure the demand uncertainty that a firm faces and show that this measure may help to explain the variation in inventory performance.
Open Access
Experimental Results Indicating Lattice-Dependent Policies May Be Optimal for General Assemble-To-Order Systems
(Wiley-Blackwell, 2016) Nadar, E.; Akan, M.; Scheller Wolf, A.
We consider an assemble-to-order (ATO) system with multiple products, multiple components which may be demanded in different quantities by different products, possible batch ordering of components, random lead times, and lost sales. We model the system as an infinite-horizon Markov decision process under the average cost criterion. A control policy specifies when a batch of components should be produced, and whether an arriving demand for each product should be satisfied. Previous work has shown that a lattice-dependent base-stock and lattice-dependent rationing (LBLR) policy is an optimal stationary policy for a special case of the ATO model presented here (the generalized M-system). In this study, we conduct numerical experiments to evaluate the use of an LBLR policy for our general ATO model as a heuristic, comparing it to two other heuristics from the literature: a state-dependent base-stock and state-dependent rationing (SBSR) policy, and a fixed base-stock and fixed rationing (FBFR) policy. Remarkably, LBLR yields the globally optimal cost in each of more than 22,500 instances of the general problem, outperforming SBSR and FBFR with respect to both objective value (by up to 2.6% and 4.8%, respectively) and computation time (by up to three orders and one order of magnitude, respectively) in 350 of these instances (those on which we compare the heuristics). LBLR and SBSR perform significantly better than FBFR when replenishment batch sizes imperfectly match the component requirements of the most valuable or most highly demanded product. In addition, LBLR substantially outperforms SBSR if it is crucial to hold a significant amount of inventory that must be rationed.
Open Access
Fair allocation of in-kind donations in post-disaster phase
(2024-05) Varol, Zehranaz
Disaster response aims to address the immediate needs of the affected populations quickly in highly uncertain circumstances. In disaster relief supply chains, the demand comes from disaster victims (typically considered as internally dis-placed populations), while the supply mostly consists of in-kind donations. This dissertation focuses on finding a fair mechanism to distribute a scarce relief item among a set of demand points under supply uncertainty. Primary concerns, restrictive elements, and unknown parameters change throughout the response phase, which substantially affects the structure of the underlying problems. Thus, the first part of this study provides a temporal classification of disaster response (e.g., into subphases) based on evolving features of demand and supply. As the next step, a donation management problem is structured considering the characteristics of a selected subphase. We first focus on the deterministic donation management problem, which is formulated as a multi-criteria multi-period location-inventory problem with service distance constraints. A set of mobile facilities, called points of distribution (PoDs), is used to distribute the collected supply. In particular, two decisions are made for every period of the planning horizon: (i) where to locate a limited number of mobile PoDs and (ii) what quantity to deliver to each demand node from each PoD. We consider three criteria. The first two involve the so-called deprivation cost, which measures a population’s “suffering” due to a shortage. The third objective is related to the total travel time. Two resulting vectorial optimization models are solved using the ε-constraint method, and the corresponding Pareto frontiers are obtained. Computational results are presented that result from applying the proposed methodological developments to an instance of the problem using real data as well as a generated one. Finally, the stochastic counterpart of the problem is addressed with the aim of minimizing a deprivation cost-based objective. The uncertain supply parameters are integrated into the model using a multi-stage stochastic programming (MSSP) approach. The MSSP model is tested on a real data set to assess and evaluate possible policies that can be adopted by decision-makers. Two matheuristic approaches are employed to handle the exponential growth of the scenario trees: a rolling horizon algorithm and a scenario tree reduction algorithm. A set of computational experiments is performed to evaluate the performance of the proposed methodologies. Overall, the results show that the proposed algorithms can better support the decision-making process when fairness is of relevance.
Open Access
Financial Hedging and Optimal Procurement Policies under Correlated Price and Demand
(Wiley-Blackwell, 2017) Goel, A.; Tanrisever, F.
We consider a firm that procures an input commodity to produce an output commodity to sell to the end retailer. The retailer's demand for the output commodity is negatively correlated with the price of the output commodity. The firm can sell the output commodity to the retailer through a spot, forward or an index-based contract. Input and output commodity prices are also correlated and follow a joint stochastic price process. The firm maximizes shareholder value by jointly determining optimal procurement and hedging policies. We show that partial hedging dominates both perfect hedging and no-hedging when input price, output price, and demand are correlated. We characterize the optimal financial hedging and procurement policies as a function of the term structure of the commodity prices, the correlation between the input and output prices, and the firm's operating characteristics. In addition, our analysis illustrates that hedging is most beneficial when output price volatility is high and input price volatility is low. Our model is tested on futures price data for corn and ethanol from the Chicago Mercantile Exchange.
Open Access
The impact of abusing return policies: a newsvendor model with opportunistic consumers
(Elsevier, 2018) Ülkü, M. A.; Gürler, Ülkü
Consumers may return a product for a variety of reasons, such as the product having the wrong color or size, having poor functionality, being damaged during shipment, or simply prompting regret for an impulsive purchase. Retailers generally provide lenient return policies not only because they may signal high quality but also because they act as risk relievers for consumers’ purchasing decision processes. However, increasing product returns have become particularly challenging for the efficient management of inventory. As such, at the crux of a holistic inventory model lies the understanding of consumer return behavior. In this study, we introduce a variant of the classical single-period inventory (newsvendor) model with returns, in which heterogeneous consumers decide, based on their post-purchase valuation of the product, whether to return the product after using it. From the perspective of the retailer, such deliberate returns may abuse the return policy, which in turn may exacerbate reverse logistics and environmental costs. To that end, we incorporate demand uncertainty and consumer valuation uncertainty by explicitly gauging return probabilities and differentiated salvage values into a newsvendor model. We derive analytical results for the profit-maximizing order quantity for a single-period product that comes with a retailer return policy and exclusively identify the impact of return type as abused or normal. Also offered are closed-form optimal solutions in the cases where market demand is exponentially or uniformly distributed. Structural and numerical results lend managerial insight into how optimal ordering amount, profit, return rates and salvage values change with the price, return window, and hassle cost of returning the product.
Open Access
An inventory management system for Özaltın Construction and Trading Company
(1992) Özaltın, Aytuğ
This study basically deals with establishing an inventory management system for Ozaltin Construction and Trading Company. It is aimed at improving the inventory control system through better allocation of operating funds and managerial efforts to the items in the inventory. The study starts with a classification system, where items are ranked in descending order of importance. The classification criteria are conditions of supply, consumption and storage, and the monetary usage rate of the items. The categorization highlights the items in inventory that really require the necessary attention. The rest of the study deals with various decision systems for these items on when to place an order. Considering the increases in inventory holding costs, as well as the penalties of delaying a job, it is clear that even small improvements will yield to considerable amount of savings.
Open Access
Inventory performance with pooling: evidence from mergers and acquisitions
(Elsevier, 2015) Çömez-Dolgan, N.; Tanyeri B.
Theoretical studies show that compared to decentralized inventory management, (i) pooling inventories for different demand sources decreases the optimal safety stock, which in turn decreases inventory costs and (ii) the decrease in stock is related to the correlation between the different demand sources and variabilities of demands. Mergers and acquisitions (M&A) provide a business context to investigate the effects of correlation and variability of the merging firms' demands on potential improvements in inventory performance through inventory pooling. While merging firms may not fully centralize their inventory decisions, the coordination of inventory and supply chain decisions may result in synergies. Using firm-level data for 270 same-industry mergers carried out in U.S. between 1981 and 2009, we find that the inventory turnover of bidder and target firms improves (relative to firms in their industry) following the successful completion of mergers. The improvement in turnover is especially pronounced in deals where the demand of bidder and target firms are negatively correlated prior to the merger. Our results provide novel empirical support for the predictions of theoretical models on inventory economies in M&A.
Open Access
Multicriteria ABC classification with AHP method: an application
(1996) Erdinç, Emrah
The traditional ABC classification is an inventory management technique that is applied by many companies in different industries. The method classifies the items in the inventory as class A. B. and C. The classification enables the managers to exert different levels of control on each class according to their importance for the company. Class A is constituted of the most important items and class C is constituted of the least important ones. Class B items have intermediate importance for the company. The Traditional ABC Classification method uses only one criterion in order to classify the items, however management may need to consider multiple criteria. The Multicriteria ABC Classification method provides a solution to this problem. This method also enables the managers to incorporate their judgments into the analysis. In this thesis both the traditional and the multicriteria ABC classification methods are applied to the inventory of a Turkish pharmaceutical company and the results are compared. The Analytic Hierarchy Process (AHP) technique is utilized in order to conduct the multicriteria inventory classification.
Open Access
Real time selection of scheduling rules and knowledge extraction via dynamically controlled data mining
(Taylor & Francis, 2010) Metan, G.; Sabuncuoglu, I.; Pierreval, H.
A new scheduling system for selecting dispatching rules in real time is developed by combining the techniques of simulation, data mining, and statistical process control charts. The proposed scheduling system extracts knowledge from data coming from the manufacturing environment by constructing a decision tree, and selects a dispatching rule from the tree for each scheduling period. In addition, the system utilises the process control charts to monitor the performance of the decision tree and dynamically updates this decision tree whenever the manufacturing conditions change. This gives the proposed system the ability to adapt itself to changes in the manufacturing environment and improve the quality of its decisions. We implement the proposed system on a job shop problem, with the objective of minimising average tardiness, to evaluate its performance. Simulation results indicate that the performance of the proposed system is considerably better than other simulation-based single-pass and multi-pass scheduling algorithms available in the literature. We also illustrate knowledge extraction by presenting a sample decision tree from our experiments.
Open Access
Resource recovery management using inventory models and supply contracts: An application to leaded waste recovery
(International Society for Environmental Information Sciences, 2005) Gunalay, Y.; Yeomans J.S.
Several recent studies have shown that significant quantities of leaded wastes recovered from the disposal of television cathode ray tubes (CRTs) will be entering the waste stream over the next 50 years in a form that is ideal for post-consumer remanufacturing. Furthermore, numerous countries have recently enacted legislation requiring industrial systems to engage in the practice of industrial ecology by having all discarded, returned, or otherwise spent products from manufacturing processes become raw material inputs in subsequent manufacturing operations. Therefore legislation banning CRT disposal together with mandated remanufacturing requirements could lead to numerous potentially attractive business ventures for reprocessing and recycling the high lead content found in this waste. This paper examines inventory issues related to the effective management of these leaded CRT wastes and the nature of the waste flows is considered from the perspective of different management options for inventory control through the use of supply contracts. An effective inventory management policy is extremely important when there is great uncertainty and variability in the year-to-year or within-year quantity of product available - as is the case with the supply of CRT wastes. If it is anticipated that a high percentage of the waste stream will be utilized, then an effective inventory policy proves absolutely essential - but also proves to be an extremely complex process. Consequently, the supply contract approach can be employed to reconcile different pricing preferences with the varying delivery time horizons of different customers. © 2005 ISEIS - International Society for Environmental Information Sciences .
Open Access
Safety stock placement for serial systems under supply process uncertainty
(Springer, 2020) Urlu, B.; Erkip, Nesim K.
In this study, we address safety stock positioning when demand per period is a known constant but supply is uncertain. The supply is either available or not available, while the setting is that of a periodically reviewed, serial system following a base stock policy. Each stage is allowed to operate according to the guaranteed or stochastic service model. We use a Discrete Time Markov Chain model for expressing the expected on-hand inventories for each stage, along with other terms of interest, as a function of policy parameters determined by a given service level requirement for the end product. Exact models are constructed for single-stage and two-stage systems. As the number of states for a two-stage system grows exponentially, we propose an approximation for expressing the effect of the input stage using a single parameter. A generalization for the approximation is provided for a multi-stage problem. Computational evaluations of the approximation, as well as numerical comparisons of different cases, are presented.
Open Access
Spare parts inventory management with demand lead times and rationing
(Taylor & Francis, 2007) Koçaǧa, Y. L.; Şen, A.
We study an inventory system that consists of two demand classes. The orders in the first class need to be satisfied immediately, whereas the orders in the second class are to be filled in a given demand lead time. The two classes are also of different criticality. For this system, we propose a policy that rations the non-critical orders. Under a one-for-one replenishment policy with backordering and for Poisson demand arrivals for both classes, we first derive expressions for the service levels of both classes. The service level for the critical class is an approximation, whereas the service level for the non-critical class is exact. We then conduct a computational study to show that our approximation works reasonably, the benefits of rationing can be substantial, and the incorporation of demand lead time provides more value when the demand class with demand lead time is the critical class. The research is motivated by the spare parts service system of a major capital equipment manufacturer that faces two types of demand. For this company, the critical down orders need to be satisfied immediately, while the less critical maintenance orders can be satisfied after a fixed demand lead time. We conduct a case study with 64 representative parts and show that significant savings (as much as 14% on inventory on hand) are possible through incorporation of demand lead times and rationing.
Open Access
Supporting hurricane inventory management decisions with consumer demand estimates
(Elsevier B.V., 2016) Morrice, D. J.; Cronin, P.; Tanrisever, F.; Butler, J. C.
Matching supply and demand can be very challenging for anyone attempting to provide goods or services during the threat of a natural disaster. In this paper, we consider inventory allocation issues faced by a retailer during a hurricane event and provide insights that can be applied to humanitarian operations during slow-onset events. We start with an empirical analysis using regression that triangulates three sources of information: a large point-of-sales data set from a Texas Gulf Coast retailer, the retailer's operational and logistical constraints, and hurricane forecast data from the National Hurricane Center (NHC). We establish a strong association between the timing of the hurricane weather forecast, the forecasted landfall position of the storm, and hurricane sales. Storm intensity is found to have a weaker association on overall inventory decisions. Using the results of the empirical analysis and the NHC forecast data, we construct a state-space model of demand during the threat of a hurricane and develop an inventory management model to satisfy consumer demand prior to a hurricane making landfall. Based on the structure of the problem, we model this situation as a two-stage, two-location inventory allocation model from a centralized distribution center that balances transportation, shortage and holding costs. The model is used to explore the role of recourse, i.e., deferring part of the inventory allocation until observing the state of the hurricane as it moves towards landfall. Our approach provides valuable insights into the circumstances under which recourse may or may not be worthwhile in any setting where an anticipated extreme event drives consumer demand.