• Environmental and Resource Economics Review
• /
• v.11 no.3
• /
• pp.447-463
• /
• 2002

The heat demand prediction is an essential issue in management of district heating system. Without an accurate prediction through the lead-time period, it might be impossible to make a rational decision on many issues such as heat production scheduling and heat exchange among the plants which are very critical for the district heating company. The heat demand varies with the temperature as well as the time nonlinearly. And the parametric specification of the heat demand model would cause a misspecification bias in prediction. A nonparametric model for the short-term heat demand prediction has been developed as an alternative to avoiding the misspecification error and tested with the actual data. The prediction errors are reasonably small enough to use the model to predict a few hour ahead heat demand.

• Journal of the Korea Safety Management & Science
• /
• v.15 no.1
• /
• pp.217-229
• /
• 2013

As customers' demands for diversified small-quantity products have been increased, there have been great efforts for a firm to respond to customers' demands flexibly and minimize the cost of inventory at the same time. To achieve that goal, in SCM perspective, many firms have tried to control the inventory efficiently. We present an mathematical model to determine the near optimal (s, S) policy of the supply chain, composed of multi suppliers, a warehouse and multi retailers. (s, S) policy is to order the quantity up to target inventory level when inventory level falls below the reorder point. But it is difficult to analyze inventory level because it is varied with stochastic demand of customers. To reflect stochastic demand of customers in our model, we do the analyses in the following order. First, the analysis of inventory in retailers is done at the mathematical model that we present. Then, the analysis of demand pattern in a warehouse is performed as the inventory of a warehouse is much effected by retailers' order. After that, the analysis of inventory in a warehouse is followed. Finally, the integrated mathematical model is presented. It is not easy to get the solution of the mathematical model, because it includes many stochastic factors. Thus, we get the solutions after the stochastic demand is approximated, then they are verified by the simulations.

• Industrial Engineering and Management Systems
• /
• v.3 no.1
• /
• pp.52-58
• /
• 2004

This report examines the issue of designing an efficient production system by increasing several types of flexibility. Increasing manufacturing flexibility is a key strategy for efficiently improving market responsiveness in the face of uncertain market demand for final products. The manufacturing system comprises multiple plants, of which individual plants have multiple manufacturing lines that are designed to produce limited types of products in accordance with their size and materials. Imbalance in the workload occurs among plants as well as among manufacturing lines because of fluctuations in market demand for final products. Thereby, idleness of some manufacturing lines and longer lead times in some manufacturing lines occur as a result of the high workload. We clarify how these types of flexibility affect manufacturing performance by improving only one type of flexibility or by improving multiple types of flexibility simultaneously. The average lead time and the imbalance in workload are adopted as measures of manufacturing performance. Three types of manufacturing flexibility are interrelated: machine flexibility, routing flexibility, and process flexibility. Machine flexibility refers to the various types of operations that a machine can perform without requiring the prohibitive effort of switching from one order to another. Routing flexibility is the capability of processing a given set of part types using more than one line (alternative line) in the plant. Process flexibility results from being able to build different types of final products at the same plant.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.35 no.2
• /
• pp.138-146
• /
• 2012

This paper studies the effect of information quality level and customer demand on performance measures in a supply chain. The information quality level compares 2 types, the information levels of a customer demand and a lead time. The customer demand process follows a general auto-correlated AR(1) process without seasonality. In the AR(1) process, ${\sigma}$ indicates the degree of demand fluctuation and ${\rho}$ means the trend of customer demand. ANOVA tests using a 5% significance level are performed in SPSS to examine significant performance changes among various cases.

• Journal of Distribution Science
• /
• v.10 no.9
• /
• pp.5-11
• /
• 2012

Purpose - The objective of the paper is to explain both the price sensitivity of international tourists to South Korea and the price sensitivity of Korean tourists to international travel. The study examines long-run equilibrium relationships and Granger causal relationships between foreign exchange rates and inbound and outbound tourism demand in South Korea. Research design/ data / methodology - The study employs monthly time series data from January 1990 to September 2010. The paper examines the long-run equilibrium relationship using the Johansen cointegration test approach after unit root tests. The short-run Granger causality was tested using the vector error correction model with the Wald test. Results - Hypothesis 1 testing whether there is a long-run equilibrium relationship between exchange rates, inbound and outbound tourism demand is supported. Hypothesis 2 testing whether exchange rates lead to a change in touristarrivals and expenditure is not supported. Hypothesis 3 testing whether exchange rates lead to a change in tourist departures and expenditure is supported. Conclusions - The findings of this study show that the impacts of tourism price competitiveness are changing quite significantly with regard to destination competitiveness. In other words, the elasticity of tourism price over tourism demand has been moderated.

• Proceedings of the Society of Korea Industrial and System Engineering Conference
• /
• 2002.05a
• /
• pp.349-357
• /
• 2002

This research is basically deals with an inventory distribution system with several regional sales branches. Under the continuous review policy, each sales branch places an order to its supplier whenever on hand plus on order inventory falls on the order point, and the order quantity is received after elapsing a certain lead time. This research first shows the method how to apply the product with low lever of demand into the continuous review policy. For the application, we use an order level as the maximum level of inventory during an order cycle. Also we analyze the lost sales case as a customer behavior. Further we use variable demands and variable lead times for more realistic situation. Based on the above circumstances, the research mainly discusses those methods to decide the optimal order level, order point, and order quantity for each sales branch which guarantees the system wide goal level of service, while keeping the minimum level of the system wide total inventory.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.25 no.3
• /
• pp.78-84
• /
• 2002

This research is basically deals with an inventory distribution system with several regional sides branches. Under the continuous review policy, each sales branch places an order to its supplier whenever on hand plus on order inventory falls on the order point, and the order quantity is received after elapsing a certain lead time. This research first shows the method how to apply the product with low lever of demand into the continuous review policy. For the application, we use an order level as the maximum level of inventory during an order cycle. Also we analyze the lost sales case as a customer behavior. Further we use variable demands and variable lead times for more realistic situation. Based on the above circumstances, the research mainly discusses those methods to decide the optimal order level, order point, and order quantity for each sales branch which guarantees the system wide goal level of service, while keeping the minimum level of the system wide total inventory.

• Culinary science and hospitality research
• /
• v.5 no.1
• /
• pp.89-101
• /
• 1999

This study attempts to identify the most accurate quantitative forecasting technique for measuring the future level of demand for food ＆ beverage in super deluxe hotel in Seoul, which will subsequently lead to determining the optimal level of purchasing food ＆ beverage. This study, in detail, examines the food purchasing system of H hotel, reviews three rigorous univariate time series models and identify the most accurate forecasting technique. The monthly data ranging from January 1990 to December 1997 (96 observations) were used for the empirical analysis and the 1998 data were left for the comparison with the ex post forecast results. In order to measure the accuracy, MAPE, MAD and RMSE were used as criteria. In this study, Box-Jenkins model was turned out to be the most accurate technique for forecasting hotel food ＆ beverage demand among selected models generating 3.8％ forecast error in average.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.10a
• /
• pp.355-360
• /
• 2000

Recently, to be satisfied the consumer's demand the life cycle and the lead time of product is to be shorted. So it is important to reduce the time and cost in manufacturing prototypal mold. These days, in order to reduce the lead time and cost high speed machining is highlighted. In the paper, using the high speed machining and aluminum-7075, the fundamental experiment is implemented in the change of cutting force, machining time, surface characteristic according to the tool path. And then the prototypal mold of the automatic knob is machined.

• Proceedings of the Korea Association of Information Systems Conference
• /
• 2000.11a
• /
• pp.36-44
• /
• 2000

The purpose of this study is to introduce a more efficient forecasting technique, which could help result the reduction of cost in removing the waste of airline in-flight meals. We will use a neural network approach known to many researchers as the “Outstanding Forecasting Technique”. We employed a multi-layer perceptron neural network using a backpropagation algorithm. We also suggested using other related information to improve the forecasting performances of neural networks. We divided the data into three sets, which are training data set, cross validation data set, and test data set. Time lag variables are still employed in our model according to the general view of time series forecasting. We measured the accuracy of our model by “Mean Square Error”(MSE). The suggested model proved most excellent in serving economy class in-flight meals. Forecasting the exact amount of meals needed for each airline could reduce the waste of meals and therefore, lead to the reduction of cost. Better yet, it could enhance the cost competition of each airline, keep the schedules on time, and lead to better service.