• Journal of Korean Society for Quality Management
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• v.38 no.3
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• pp.333-339
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• 2010

It is difficult to determine an optimal inventory level of aircraft engine and modules to achieve the target operational availability since F100-PW-200 & 229 engines of the F-16 & KF-16 aircraft are consisted of 5 modules with different failure rates and costs. This study presents a decision model, combining an integer programming problem and a regression metamodel. Data for the metamodel was attained from results of a simulation model, that represents operational and repair process of F-16 and KF-16. The objective function of an integer programming problem is maximizing the operational availability, representing pessimistic circumstances. Finally, an integer programming problem with a metamodel can make an optimal decision of the inventory level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.105-111
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• 2017

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers' are assumed to have the common cycle time, and a vendor manages retailers' inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor's cost, retailer's cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.2
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• pp.81-86
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• 2014

In this paper, a jointly optimal group replacement and spare provisioning policy is presented. Most maintenance policies assume that the spare inventory is always available, but in practice the maintenance schedule is affected by the availability of spare inventory. We present a maintenance-inventory model which jointly optimizes the group replacement interval and spare ordering quantity. Group replacement policy is used when a group of units are put in operation simultaneously. The operating fleet is replaced altogether at a predetermined number of units are failed. A sufficient level of spare inventory is carried to perform a number of group replacement. A cost rate expression which considers the group maintenance cost and inventory holding cost is derived and a heuristic method for searching the optimum value of decision variables is suggested. Numerical examples demonstrate the analytical results and the performance of the presented model.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.3
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• pp.416-424
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• 2019

This paper studies the optimal inventory levels of P-3 assemblies in order to assure the required operational availability. A simulation model is developed for identifying the impact of the inventory levels on operational availability. Based on the result of the simulation model, multiple regression analysis is performed. Finally, the optimal inventory levels of critical P-3 assemblies are determined with integer programming. Additionally, sensitivity analysis of depot maintenance period is also conducted for its impact on the operational availability.

• The Journal of Fisheries Business Administration
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• v.30 no.2
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• pp.25-37
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• 1999

Some multi echelon inventory systems carry perishable products. The value of these product reduces as the period of time they spend in the system. In this paper We derive the necessary condition to determine optimal quantity, service level for a perishable product. The systems considered consist of two echelons and carry single item. To determine the optimal order quantity, the demand is assumed to be constant, the holding costs may be different in the echelons, and it allows no shortages. I assumed the price of product decreases by negative exponential function. To determine service level, following assumptions used in the model ㆍlead time is constant. ㆍdemand is normal distribution. ㆍthe product starts to perish at the second echelon. Service level is computed for different levels of lead times and for different variance of demands and for different price functions. The experimental results indicate that the service level in cost is a function of service level in demand and perishability of product. Results of the models exhibit that perishability and the age of the product are critical to determine the lot sizing and service level.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.1-10
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• 2015

In this paper, we consider multi-item inventory management. When managing a multi-item inventory, we coordinate replenishment orders of items supplied by the same supplier. The associated problem is called the joint replenishment problem (JRP). One often-used approach to the JRP is to apply a can-order policy. Under a can-order policy, some items are re-ordered when their inventory level drops to or below their re-order level, and any other item with an inventory level at or below its can-order level can be included in this order. In the present paper, we propose a method for finding the optimal parameter of a can-order policy, the can-order level, for each item in a lost-sales model. The main objectives in our model are minimizing the number of ordering, inventory, and shortage (i.e., lost-sales) respectively, compared with the conventional JRP, in which the objective is to minimize total cost. In order to solve this multi-objective optimization problem, we apply a genetic algorithm. In a numerical experiment using actual shipment data, we simulate the proposed model and compare the results with those of other methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.25-36
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• 1997

The purpose of this paper is to structure a new integrated model that can minimize the total cost for the transportation and inventory systems between m origin points, where origin i has a supply of a commodity, such as distribution centers or warehouses, and n destination points, where destination j requires the commodity. In this case, demands of the destination points are assumed random variables which have a known probability distribution. We will find optimal distribution centers which transport the commodity to the destination points and suggest optimal inventory policy to the selected distribution center which find the optimal pair $$ and safety stock level that minimize total cost with back-ordered case. This new model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and program and provides numerical examples.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.187-198
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• 2008

There are usually plenty of material inventories in a construction site. More inventories can meet unexpected demands, and also they may have an economical advantage by avoiding a probable escalation of raw material costs. On the other hand, these inventories also cause negative aspects to increase costs for storing redundant inventory as well as decreasing construction productivity. Therefore, a proper method of deciding an optimal level of material inventories while considering dynamic variations of resources under uncertainty is very crucial for the economical efficiency of construction projects. This research presents a stochastic modelling method for construction operations, particularly targeting a work process involving on-site fabrication of raw materials like iron-rebar process (delivery, cut and assembly, and placement). To develop the model, we apply the concept of factory physics to depict the overall components of a system. Then, an optimal inventory management model is devised to support purchase decisions where users can make timely actions on how much to order and when to buy raw materials. Also, optimal time lag, which minimizes the storage time for pre-assembled materials, is obtained. To verify this method, a real case is applied to elicit an optimal amount of inventory and time lag. It is found that average values as well as variability of inventory level decreased significantly so as to minimize economic costs related to inventory management under uncertain project condition.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.267-284
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• 2008

Consider a supply chain where products are produced at a manufacturing system, shipped to a distribution center, and then supplied to customers. The distribution center controls inventory based on a base-stock policy, and whenever a unit of product is demanded by a customer, an order is released to the production system. Unsatisfied demand is backordered, and the inventory and backordered units are a function of the base-stock level. The manufacturing system is modeled as an M/M/s/c queueing system, and orders exceeding the limited buffer capacity are blocked and lost. The throughput of the manufacturing system and the steady state distribution of the outstanding orders are functions of number of servers and buffers of the manufacturing system. There is a profit obtained from throughput and costs due to servers and buffers of the manufacturing system, and also costs due to inventory positions of the distribution center, and we want to maximize the total production profit minus the total cost of the supply chain by simultaneously determining the optimal number of servers and buffers of the manufacturing system and the optimal base-stock level of the distribution center. We develope two algorithms, one analytical but without guarantee of the optimal solution and one optimal but without complete analytical proofs. The problem integrates strategic problem of the manufacturing system with tactical problem of the distribution center in a supply chain.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.42
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• pp.31-38
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• 1997

The main objective of this research is to develop a model to select the optimal input service level for a distribution center - multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time. Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service level for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.