• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.83-89
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• 2004

In this paper MIP(mean inventory period) Model and OMMIP decision flow have been developed. MIP model can calculate mean inventory period which is subject to the order quantity alternative plan. OMMIP decision flow leads how can decide the most minimized order quantity in mean inventory period among various order quantity alternatives. This paper also suggests how to select the order quantity with minimum inventory period as optimal order quantity by means of comparison each mean inventory period with other mean inventory period, after simulating EOQ and order quantity of OMMIP calculated in MIP model.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.532-541
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• 1997

This article derives an analytic solution to determine the optimal size of multiple noncontinuous process and storage units. The total cost to be minimized consists of the setup cost of noncontinuous processing units and the inventory holding cost of feedstock/product storages. A novel approach, which is called PSW(Periodic Square Wave) model, is applied to represent the material flow among non-continuous units and storages. PSW model presumes that the material flow between unit and storage is periodic square wave shaped. The resulting optimal unit size has similar characteristics with the classical economic lot sizing model such as EOQ(Economic Order Quantity) or EPQ(Economic Production Quantity) model in a sense that the unit size is determined as the balance between setup and inventory holding cost. However, the influence of inventory holding cost of PSW model is different from that of EOQ/EPQ model. EOQ/EPQ model includes only the product inventory holding cost but PSW model includes all inventory holding costs around the non-continuous unit with proportional contribution. PSW model is suitable for analyzing interlinked process-storage system. The optimal lot size of PSW model is smaller than that of EOQ/EPQ model. This is quitea remarkable result considering that the EOQ/EPQ model has been is widely used since last half century.

• Journal of information and communication convergence engineering
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• v.19 no.4
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• pp.221-227
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• 2021

An early warning system was developed to help identify stock status as early as possible. For performance to improve, there needs to be a feature to predict the amount of stock that must be provided and a feature to estimate when to buy goods. This research was conducted to improve the inventory early warning system and optimize the Reminder Block's performance in minimum stock settings. The models used in this study are the single exponential smoothing (SES) method for prediction and the economic order quantity (EOQ) model for determining the quantity. The research was conducted by analyzing the Reminder Block in the early warning system, identifying data needs, and implementing the SES and EOQ mathematical models into the Reminder Block. This research proposes a new Reminder Block that has been added to the SES and EOQ models. It is hoped that this study will help in obtaining accurate information about the time and quantity of repurchases for efficient inventory management.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.457-468
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• 1997

The present paper deals with an economic order quan-tity model for items deteriorating at some constant rate with demand changing at a known and at a random point of time in the fixed pro-duction cycle.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.13-26
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• 1992

Set-up reduction is an important aspect of the Japanese Just-In-Time (JIT) and Zero Inventory (ZI) concepts. In this paper, we first analyze the effects of set-up cost reduction on tatal inventory, average lot size and forecast horizon in the dynamic lot size model. We also examine the various effects of set-up cost reduction in the EOQ model and explain why many Japanese firms try to cut set-up cost and/or set-up time greatly.

• Korean Management Science Review
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• v.32 no.1
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• pp.65-82
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• 2015

Purchase dependence is a frequent phenomenon in retail shops and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. Since purchase dependence is an important factor in designing inventory replenishment policies, this paper demonstrates the means of applying it to the partial backordering inventory model. Through computational analyses, this paper compares the performance of inventory models that either consider or ignore purchase dependence; the results demonstrate that inventory models that ignore purchase dependence incur more average cost per unit time than the model that considers purchase dependence, and the impact of purchase dependence can increase in significance as the item set becomes more closely correlated with regard to order demand.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.70-78
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• 2020

Under the situation which customer orders are cancelled unless all products in the order are delivered all at once, this paper concentrates on the purchase dependent demands and explores the systematic approach to implant the purchase dependence into the multi-product inventory model. First, by acknowledging that it is a challenging task to formulate a suitable inventory model for the purchase dependence, we derive the optimal solution condition using an EOQ model and extend the optimal solution condition to periodic review models. Then, through the comparison simulation of four inventory policies regarding several degrees of purchase dependence, we demonstrate that the inventory models which consider the purchase dependence generate less total cost than the inventory models which ignore the purchase dependence. In general, the inventory models which consider the purchase dependence reduce the loss of sales by maintaining more inventories, which results in reducing the total cost. Consequently, the simulation result supports the effectiveness of this paper's approach. In addition, this paper uses the individual order period and joint order period obtained from the EOQ model for the multi-product inventory model. Through the in-depth analysis of comparing the two models, we observe that the model of using the joint order period produces less total cost when the degree of purchase dependence is high, but the model of using the individual order period produces less total cost when the degree of purchase dependence is low.

• Management Science and Financial Engineering
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• v.18 no.1
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• pp.21-26
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• 2012

Two previous studies that attempted to generalize the deterministic joint pricing-inventory decision model are reevaluated. We prove analytically that even in a single-product environment, the EOQ model with constant priceelastic demand cannot find optimal solutions unless two optimality conditions associated with price elasticity and demand magnitude are satisfied. Due to the inexistence of the general optimality for the problem, demand function and price elasticity must be evaluated and bounded properly to use the methods proposed in the previous studies.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.35-53
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• 2007

We consider a(worst-case) robust optimization version of the Economic Order Quantity(EOQ) model. Order setup costs and inventory carrying costs are assumed to have uncertainty in their values, and the uncertainty description of the two parameters is supposed to be given by an ellipsoidal representation. A genetic algorithm combined with Monte Carlo simulation is proposed to approximate the ellipsoidal representation. The objective function of the model under ellipsoidal uncertainty description is derived, and the resulting problem is solved by another genetic algorithm. Computational test results are presented to show the performance of the proposed method.

• 한국디지털정책학회:학술대회논문집
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• 2007.06a
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• pp.349-357
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• 2007

We consider supply chain which consist of one manufacturer, one distributor and N retailers for a single product. This paper determines inventory replenishment period of supply chain using houristic method and propose order policy through re-coordination of inventory replenishment. Also, We develops inventory management model to calculate total cost of supply chain under assumptions of constant demand. The computational results show that the proposed inventory replenishment period and inventory management model is efficient.