• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.3
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• pp.50-57
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• 2003

In this paper, we consider an integrated inventory system where a single supplier purchases and processes raw materials in order to deliver finished goods to a single buyer for effective implementation of Just-In-Time purchasing. An integrated JIT lot-splitting model of facilitating multiple shipments in small lots is developed in a JIT purchasing environment. Also, an iterative solution procedure is developed to find the order quantity for the finished goods and raw materials, and the number of shipments between buyer and supplier. We show by example that the integrated policy adopted by both buyer and supplier in a cooperative manner can provide them a greater economic benefit than seeking the local optimal inventory policy independently.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.2
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• pp.57-65
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• 2009

In continuous review inventory model, (${\varrho}$, ${\gamma}$) system, order quantity(${\varrho}$) and reorder point(${\gamma}$) should be determined to calculate inventory-related cost that consists of setup, holding, and penalty costs. The procedure to obtain the exact value of ${\varrho}$ and ${\gamma}$ is complex. In this paper, a regression analysis is proposed to get the approximate inventory-related cost without the determination of ${\varrho}$ and ${\gamma}$ in the case that the standard deviation(${\sigma}$) of the lead time demand is small or that the mean(${\mu}$) of the lead time demand is proportional to ${\sigma}$. To save inventory-related cost, central warehouses with (${\varrho}$, ${\gamma}$) system can be built. Central warehouse can provide some stores with products with the consideration of the tradeoff between inventory-related cost and transportation cost. The number and the location of central warehouses to cover all the stores are determined by a regression-based approach. The performance of the proposed approach is tested by using some computational experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.2
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• pp.91-106
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• 1992

It an inventory control system, the demand over time are often assumed to be independently identically distributed (i. i. d.). However, the demands may well be correlated over time in many situations. The estimation of reorder points is not simple for correlated demands with variable lead time. In this paper, a general class of autoregressive and moving average processes is considered for modeling the demands of an inventory item. The first four moments of the lead-time demand (L) are derived and used to approximate the distribution of L. The reorder points at given service level are then estimated by the three approximation methods : normal approximation, Charlier series and Pearson system. Numerical investigation shows that the Pearson system and the Charlier series performs extremely well for various situations whereas the normal approximation show consistent underestimation and sensitive to the distribution of lead time. The same conclusion can be reached when the parameters are estimated from the sample based on the simulation study.

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.27-33
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• 1987

A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between cussessive unit demands as well as those between cussessive unit losses, are independently and identically distributed random variables having negative exponential distributions with respective parameters .mu. and .lambda. It is further assumed that leadtime for each order is an outstanding-order-dependent random variable. The steady state probability distribution of the net inventory level is derived under the continuous review (S -1, S) inventory policy, from which the total expected coast expression is formulated.

• Korean Management Science Review
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• v.26 no.1
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• pp.171-182
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• 2009

We consider the inventory replenishment problem and the vehicle routing problem simultaneously in the vending machine operation. This problem is known as the inventory routing problem. We design a memory cell in the clonal selection algorithm. The memory cell store the best solution of previous solved problem and use an initial solution for next problem. In general, the other clonal selection algorithm used memory cell for reserving the best solution in current problem. Experiments are performed for testing efficiency of the memory cell in demand uncertainty. Experiment result shows that the solution quality of our algorithm is similar to general clonal selection algorithm and the calculations time is reduced by 20% when the demand uncertainty is less than 30%.

• Journal of Korean Society for Quality Management
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• v.15 no.1
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• pp.55-62
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• 1987

A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between successive unit demands, as well as those between successive unit losses, are independently and identically distributed random variables having negative exponential distribution with respective parameters. We have derived the steady state probability distribution of the net inventory level assuming negative exponential delivery time under the continuous review (S-1, S) inventory policy. Also we have derived the total expected cost expression and necessary conditions to be satisfied for an optimal solution.

• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.179-191
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• 2005

Recently, Vendor Managed Inventory(VMI) has been commonly recognized as one of the supply chain application that delivers clear value to the sectors of electic & electronic components. VMI is a process in which a supplier generates orders for its distributor based on demand information sent by the distributor. VMI is providing the benefits of smoother demand, lower inventories(work in process, safety stock) and reduced costs. This study focused on improvement of safety level inventory efficiency by VMI. The results indicated that VMI allowed the company to serve its customers more surely and efficiently.

• IE interfaces
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• v.16 no.1
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• pp.111-116
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• 2003

Business integration has been considered as one of the most critical success factors that enable the firms to gain competitive edges. Despite this trend, it has also been found among not a few companies that the activities that should be functionally tied with are performed even independently. In this study, an integrated model of production planning and inventory has been developed. Computerization of the production planning activities is proposed and implemented. We also proposed the reasonable inventory levels of each item using historic data of the items, which are composed of safety stock from the given fill-rate, operating stock from the production patterns, and reserved stock from the production planning. This study has helped the firm to have clearer job definition of the related processes, to tightly control the inventory by setting and tracing the reasonable fill rates for every product, and to quickly respond to the market changes through the computerized production planning process.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.110-116
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• 2004

ABC analysis is the process of dividing inventory items into three classes according to their monetary usage so that managers can focus on items that have the highest monetary usage value, and has been widely used in practice since its development in 1950. However, the original criterion, monetary usage value, can no longer be the only rational criterion. Applying Analytic Hierarchy Process, we develop a new method to classify inventory items by considering such operationally/strategically important criteria as annual dollar usage, lead time, supplier's capacity, defective rate, difficulty of purchasing and unit price. A case study is performed applying the method to the field data from a company which produces electrochemical products.

• Journal of the Korean Operations Research and Management Science Society
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• v.4 no.1
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• pp.25-31
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• 1979

We consider the optimal ordering policy for a single-product two-stage inventory system where the main assumptions are as follows: (i) constant continuous demand only at stage 2, (ii) constant input (production) rate at stage 1, (iii) instantaneous delivery (transportation) from stage 1 to stage 2, (iv) backlogging is allowed only at stage 2, (v) an infinite planning horizon. Costs considered are ordering and linear holding costs at both stages, and linear shortage cost only at stages 2. By solving 9 different case problems, we have observed the general from of the optimal ordering policies for our model which minimizes the total cost per unit time. It is noticeable from this observation that the questionable but more often than not adopted assumption by many authors in determining the optimal potimal policy for multistage inventory systems, that the ordering (lot) sizes at each stage remain constant thruout the planning horizon, is not valid.