• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.3
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• pp.831-839
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• 2008

The steel industry is becoming more important around the world and the demand of steel is increasing. Korea is the 5th country of steel producing in the world and the attention in the steel industry is growing. The steel industry is one of the key industry in leading the economic growth in Korea. This study attempts to analyze by time-series the economic impacts of the steel industry using an inter-industry analysis Specifically, the study investigates production-inducing effect, value added inducing effect and employ-inducing effect of the steel industry based on demand-driven model and the study deals with supply shortage effect and sectoral price effect of the steel industry by using supply-driven model and Leontief price model.

• Journal of Korea Water Resources Association
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• v.30 no.1
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• pp.45-54
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• 1997

The correct estimation of the daily or hourly urban water demand is required for the efficient management and operation of the water supply facilities. The prediction of water supply demand are regression model and time series method, the optimum ARIMA (Auto Regressive Integrated Moving Average) model was sought for the daily urban water demand estimation in this paper. The data used for this study were obtained from the city of Kwangju Korea. The raw data used in this study were rearranged 15, 30, 60, 90 days for the purpose of analysis. The statistical analysis was applied to the data to obtain the ARIMA model. As a result, the parameters determining the ARIMA model was obtained. The accuracy of the model was 2% of water supply. The developed model was found to be useful for the practical operation and management of the water supply facilities.

• Korean System Dynamics Review
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• v.10 no.1
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• pp.61-76
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• 2009

We try to use system dynamics to forecast the demand/supply and price, also transportation fare for iron ore. Iron ore is very important mineral resource for industrial production. The structure for this system dynamics shows non-linear pattern and we anticipated the system dynamic method will catch this non-linear reality better than the regression analysis. Our model is calibrated and tested for the past 6 year monthly data (2003-2008) and used for next 6 year monthly data(2008-2013) forecasting. The test results show that our system dynamics approach fits the real data with higher accuracy than the regression one. And we have run the simulations for scenarios made by possible future changes in demand or supply and fare related variables. This simulations imply some meaningful price and fare change patterns.

• Korean Journal of Chemical Engineering
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• v.36 no.1
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• pp.12-20
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• 2019

An energy storage system consisting of a battery and a power-to-methanol (PtM) unit was investigated to develop an energy storage system for renewable energy systems. A nonlinear programming model was established to optimize the energy storage system. The optimal installation capacities of the battery and power-to-methanol units were determined to minimize the cost of the energy system. The cost from a renewable energy system was assessed for four configurations, with or without energy storage units, of the battery and the power-to-methanol unit. The proposed model was applied to the modified electricity supply and demand based on published data. The results show that value-adding units, such as PtM, need be included to build a stable renewable energy system. This work will significantly contribute to the advancement of electricity supply and demand management and to the establishment of a nationwide policy for renewable energy storage.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.29-41
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• 2020

Wild pollinators provide important pollination services for crops. However, their geographical ranges and impact on pollination services have not been fully explored within the scope of Korean agricultural land. This study aims to identify spatial supply-demand mismatches across orchard fields in the context of assessing pollination service risk. We first used National Ecosystem Survey data and a species distribution model (MaxEnt) to develop the geographic range of each of 32 wild pollinators belonging to three families (Diptera, Hymenoptera, and Lepidoptera). We then summed the modeled presence probability of each species to obtain a measure of spatially explicit pollinator richness. This modeled richness, defined as pollination supply, was compared with the summed area of orchard fields at the municipal boundary level to identify areas with supply-demand mismatches. The study found that Lepidoptera showed the highest species richness (8.3±1.5), followed by Hymenoptera (4.3±0.8) and Diptera (3.5±0.8) species. Median orchard area was 1.5 ㎢ (range of 0-176.7 ㎢) among 250 municipal regions in South Korea. The municipal regions were divided into three categories (tertiles) of low, middle, and high pollination supply and demand according to, respectivley, average polliator richness and orhard area. Finally, we found that 55 municipal regions (accounting for 49% of national orchard land) potentially faced high risk of pollination deficits, 81 regions (48% of national orchard land) faced intermediate risk, and 63 regions faced low risk (3% of national orchard land). In conclusion, this study revealed significant mismatch between pollination supply and demand and developed risk assessment map will guide our future efforts on pollinator habitat conservation and monitoring to conserve crop pollination services.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.97-109
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• 2014

This paper considers a reverse supply chain with simultaneous recovery of used products and manufacturing of brand-new ones. Recovered products are downgraded and have to be sold in a market different from that of brand-new products at a different price. In case of a shortage of recovered product inventory, a brand-new item, if available, can be offered at the price of a recovered product. In other words, one-way demand substitution is allowed. We address the joint decision of when to manufacture brand-new product, when to recover returned product, and how to control demand substitution to maximize the hybrid production system's profits. To this end, we propose a Markov decision Process model and investigate the structure of the optimal policy. Performance comparison is numerically implemented between the models with and without downward demand substitution option under different operating conditions of the system parameters.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.334-337
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• 2003

In this paper we presents a centralized model for a long-term replenishment contract model in the supply chain system. We assume ARIMA demand process for reflecting more realistic demand data and present a solution which minimizes total system cost of the contract model between single supplier and buyer under centralized system. From the result of experiments we can observe that the proposed model generate better result than the decentralized model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.1
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• pp.20-24
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• 2008

A bid-based pool(BBP) model is representative of energy market structure in a number of restructured electricity markets. Supply function equilibrium(SFE) models of interaction better match what is explicitly required in the bid formats of typical BBP markets. Many of the results in the SFE literature involve restrictive parametrization of the bid cost functions. In the SFE models, two parameters, intercept and slope, are available for strategic bidding. This paper addresses the realistic competition format that players can choose both parameters arbitrarily. In a fixed demand function, equilibrium conditions for generation company's profit maximization have a degree of freedom, which induces multi-equilibrium. So it is hard to choose a convergent equilibrium. However, consideration of stochastic demand function makes the equilibrium conditions independent each other based on the amount of variance of stochastic demand function. This variance provides the bidding players with incentives to change the slope parameter from an equilibrium for a fixed demand function until the slope parameter equilibrium.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.147-154
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• 2024

The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.

• Land and Housing Review
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• v.9 no.4
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• pp.10-18
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• 2018

As the volatility increasement of the number of tourist, there was been controversy over supply-demand imbalance in hotel market. The purpose of this study is to analysis on determinants of hotel occupancy rate in Jeju Island. The quantitative method is based on cointegrating regression, using an empirical dataset with hotel from 2000 to 2017. The primary results of research is briefly summarized as follows; First, there are high relationship between total hotel occupancy rate and hotel occupancy of foreign tourist. The volatility of hotel occupancy is caused by foreigner user than local tourists though local tourist high propotion of hotel occupancy in Jeju Island. Second, hotel occupancy of local tourist has not relationship with demand and supply variables. Because some hotel users are not local tourists but local resident, and effects to other variables of hotel consumer trend, accommodation such as Guest house, Airbnb. Third, there are high relationship between foreign hotel occupancy rate and demand-supply variables. These research imply that total management of supply-demand is very important to seek stability of hotel occupancy rate in Jeju Island. Also it can provide a useful solution regarding mismatch problem between supply-demand as well as development the systematic forecasting model for hotel market participants.