• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2202-2205
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• 2011

Demand side management is used to maintain the reliability of power systems and to increase the economic benefits by avoiding power plant construction. This paper presents a systematic method to calculate the quantity of seasonal demand side management using time series. A numerical example is presented to calculate the quantity of demand side management in winter season using time series.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.251-260
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• 2003

Generally, in deriving the solution of economic production quantity (EPQ) inventory model, we consider the demand rate and deterioration rate as constant quantity. But in case of real life problems, the demand rate and deterioration rate are not actually constant but slightly disturbed from their original crisp value. The motivation of this paper is to consider a more realistic EPQ inventory model with finite production rate, fuzzy demand rate and fuzzy deterioration rate. The effect of the loss in production quantity due to faulty/old machine have also been taken into consideration. The methodology to obtain the optimum value of the fuzzy total cost is derived and a numerical example is used to illustrate the computation procedure. A sensitivity analysis is also carried out to get the sensitiveness of the tolarance of different input parameters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.253-259
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• 2017

Recent development in science and technology has modernized the weapon system of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need accurate demand forecasts for spare parts. We attempted to find consumption pattern using data mining techniques. First we gathered a large amount of component consumption data through the DELIIS (Defense Logistics Intergrated Information System). Through data collection, we obtained 42 variables such as annual consumption quantity, ASL selection quantity, order-relase ratio. The objective variable is the quantity of spare parts purchased in f-year and MSE (Mean squared error) is used as the predictive power measure. To construct an optimal demand forecasting model, regression tree model, randomforest model, neural network model, and linear regression model were used as data mining techniques. The open software R was used for model construction. The results show that randomforest model is the best value of MSE. The important variables utilized in all models are consumption quantity, ASL selection quantity and order-release rate. The data related to the demand forecast of spare parts in the DELIIS was collected and the demand for the spare parts was estimated by using the data mining technique. Our approach shows improved performance in demand forecasting with higher accuracy then previous work. Also data mining can be used to identify variables that are related to demand forecasting.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.2
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• pp.79-87
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• 2005

At present Cournot model is one of the most commonly used theories to analyze the gaming situation in oligopoly market. But there exist several problems to apply this model to electricity market. The representative one is to obtain the inverse demand curve able to be induced from the relationship between market price and demand response. In Cournot model, each player offers their generation quantity to accomplish maximum profit, which is accomplished by reducing their quantity compared with available total capacity. As stated above, to obtain the probable Cournot equilibrium to reflect real market situation, we have to induce the correct demand function first of all. Usually the correlation between price and demand appears on the long-term basis through the statistical data analysis (for example, regression analysis) or by investigating consumer utility functions of several consumer groups classified as residential, industrial, and commercial. However, the elasticity has a tendency to change continuously according to the total market demand size or the level of market price. Therefore it should be updated as trading period passes by. In this paper we propose a method for inducing and updating this price elasticity of demand function for more realistic market equilibrium.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.60
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• pp.11-22
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• 2000

The main objective of this research is to analyze an order point and an order quantity of a distribution center and each branch to attain a target service level in multi-level inventory distribution system. In case of product item, we use the item with low volume of average monthly demand. Under the continuous review method, the distribution center places a particular order quantity to an outside supplier whenever the level of inventory reaches an order point, and receives the order quantity after elapsing a certain lead time. Also, each branch places an order quantity to the distribution center whenever the level of inventory reaches an order point, and receives the quantity after elapsing a particular lead time. When an out of stock condition occurs, we assume that the item is backordered. For considering more realistic situations, we use generic type of probability distribution of lead times. In the variable lead time model, the actually achieved service level is estimated as the expected service level. Therefore, this study focuses on the analysis of deciding the optimal order point and order quantity to achieve a target service level at each depot as a expected service level, while the system-wide inventory level is minimized. In addition, we analyze the order level as a maximum level of inventory to suggest more efficient way to develop the low demand item model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.93-103
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• 1995

This paper des with an economic production quantity model with partial backorders for the situation in which production lead time is deterministic and demand during lead time follows a continuous distribution. In the model, an objective function is formulated In minimize an average annual inventory cost. And then the procedure of iterative solution method for the model is developed to find both production reorder point and production quantity. Finally, sensitivity analysis for various partial backorder ratios and standard deviations of demand during production lead time are presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.59-65
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• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• Industrial Engineering and Management Systems
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• v.13 no.2
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• pp.129-147
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• 2014

This study proposes an optimal operational policy for a green supply chain (GSC) where a retailer pays an incentive for collection of used products from customers and determines the optimal order quantity of a single product under uncertainty in product demand. A manufacturer produces the optimal order quantity of product using recyclable parts with acceptable quality levels and covers a part of the retailer's incentive from the recycled parts. Here, two scenarios for the product demand are assumed as: the distribution of product demand is known, and only both mean and variance are known. This paper develops mathematical models to find how order quantity, collection incentive of used products and lower limit of quality level for recycling affect the expected profits of each member and the whole supply chain under both a decentralized GSC (DGSC) and an integrated GSC (IGSC). The analysis numerically compares the results under DGSC with those under IGSC for each scenario of product demand. Also, the effect of the quality of the recyclable parts on the optimal decisions is shown. Moreover, supply chain coordination to shift the optimal decisions of IGSC is discussed based on: I) profit ratio, II) Nash bargaining solution, and III) Combination of (I) and (II).

• The Journal of Fisheries Business Administration
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• v.41 no.2
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• pp.107-133
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• 2010

As policy makers are often concerned about dynamic effects of demand behavior and its welfare analysis by quantity changes, the paper shows how dynamic price formation systems can be built up to analyze the effect of policy options to the markets dynamically. The paper develops dynamic model of price formation for fish from the intertemporal optimization of the consumer choice problem. While the resulting model has a similar form of the error correction types of dynamic price formation system, it provides the rational demand behavior contrary to the myopic behavior of error correction demand models. The paper also develops appropriate tools of dynamic welfare analysis in quantity space using only short-run demand estimates both theoretically and empirically as a first attempt in the literature of price formation and fisheries. The empirical results of Korean fish markets show that the dynamic model and the welfare measures are reasonably plausible. The methodology and theory of this research can be applied and extended to the commodity aggregation, dynamic demand estimation, and dynamic welfare effects of regulation in the similar framework. Thus, it is hoped that this will enhance its applications to the demand-side economics.

• KIEAE Journal
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• v.7 no.2
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• pp.25-30
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• 2007

The purpose of this research is to analyze the water quantity of the rainwater detention system based on the Planning Simulation in Residential Areas. The contents of this research consists of two main parts. The first part is to calculate the supply water quantity of the rainwater detention system and the demand water quantity of the Wonheungs' ecological park. The second part is to analyze the difference between demand and supply of water quantity, based on the Planning Simulation, in the rainwater detention system. This research will contribute to the establishment of the environment-friendly site planning methods which increase the quality of residential environment in apartment housing.