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

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.34 no.10
• /
• pp.389-398
• /
• 1985

Recently maximum power demand of our country has become to be under the great in fluence of electric cooling and air conditioning demand which are sensitive to weather conditions. This paper presents the technique and algorithm to forecast the long-term maximum power demand considering the characteristics of electric power and weather variable. By introducing a weather load model for forecasting long-term maximum power demand with the recent statistic data of power demand, annual maximum power demand is separated into two parts such as the base load component, affected little by weather, and the weather sensitive load component by means of multi-regression analysis method. And we derive the growth trend regression equations of above two components and their individual coefficients, the maximum power demand of each forecasting year can be forecasted with the sum of above two components. In this case we use the coincident dry bulb temperature as the weather variable at the occurence of one-day maximum power demand. As the growth trend regression equation we choose an exponential trend curve for the base load component, and real quadratic curve for the weather sensitive load component. The validity of the forecasting technique and algorithm proposed in this paper is proved by the case study for the present Korean power system.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.56 no.2
• /
• pp.11-23
• /
• 2014

The impact and adaption on agricultural water resources considering climate change is significant for reservoirs. The change in rainfall patterns and hydrologic factors due to climate change increases the uncertainty of agricultural water supply and demand. The quantitative evaluation method of uncertainty based on agricultural water resource management under future climate conditions is a major concern. Therefore, it is necessary to improve the vulnerability management technique for agricultural water supply based on a probabilistic and stochastic risk evaluation theory. The objective of this study was to analyse the uncertainty of water resources under future climate change using probability distribution function of water supply in agricultural reservoir and demand in irrigation district. The uncertainty of future water resources in agricultural reservoirs was estimated using the time-specific analysis of histograms and probability distributions parameter, for example the location and the scale parameter. According to the uncertainty analysis, the future agricultural water supply and demand in reservoir tends to increase the uncertainty by the low consistency of the results. Thus, it is recommended to prepare a resonable decision making on water supply strategies in terms of using climate change scenarios that reflect different future development conditions.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.26 no.6
• /
• pp.757-764
• /
• 2002

Chlorination dosage in water treatment plant of field is determined by chlorination demand experiment through two or three hours after raw water was sampled in inflow. It is impossible to continuously control for real time because the sampled water is adapted chlorination dosage after water treatment process had been proceeded. Therefore in this study, we will design informal chlorination demand system, this designed system will be experimented as to water quality and accuracy of control in various conditions. Throughout these experimental results, we will revise the system and the revised system is enable to optimal control of chlorination dosage. Finally, we have developed chlorination demand system, which can automatically determination of chlorination dosage to be determined according to variety of raw water quality inflow in water treatment plant.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.96.6-96
• /
• 2001

A high peak power demand at substations will result under Moving Block Signalling (MBS) when a dense queue of trains begins to start from a complete stop at the same time in an electrified railway system. This may cause the power supply interruption and in turn affect the train service substantially. In a recent study, measures of Starting Time Delay (STD) and Acceleration Rate Limit (ARL) are the possible approaches to reduce the peak power demand on the supply system under MBS. Nevertheless, there is no well-defined relationship between the two measures and peak power demand reduction (PDR). In order to attain a lower peak demand at substations on different traffic conditions and system requirements, an expert system is one of the possible approaches to procure the appropriate use of peak demand reduction measures ...

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1947-1950
• /
• 2008

Printing technology is a very useful method in the several process of industrial fabrication due to noncontact and fast pattern generation. To make micro pattern, we investigate the electrostatic induced inkjet printer head for micro droplet generation and drop-on-demand jetting. In order to achieve the drop-on-demand micro droplet ejection by the electrostatic induced inkjet printer head, the pulsed DC voltage is supplied. In order to find optimal pulse conditions, we tested jetting performance for various bias and pulse voltages for drop-on-demand ejection. In this result, we have successful drop-on-demand operation and micro patterning. Therefore, our novel electrostatic induced inkjet head printing system will be applied industrial area comparing conventional printing technology.

• Proceedings of the KSME Conference
• /
• 2000.04b
• /
• pp.807-812
• /
• 2000

Chlorination dosage in water treatment plant of field is determined by chlorination demand experiment through two or three hours after raw water was sampled in inflow. It is impossible to continuously control fer real time because sampled water is adapted chlorination dosage after water treatment process had been proceeded. Therefore in this study, we will design informal chlorination demand system this designed system will be experimented as to water quality and accuracy of control in various conditions. Throughout these. experimental results, we will revise the system and revised system is enable to optimal control of chlorination dosage. Finally, We have developed chlorination demand system, which can automatically determination of chlorination dosage to be determined according to variety of raw water quality inflow in water treatment plant.

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

• Journal of the Korean Society of Hazard Mitigation
• /
• v.8 no.6
• /
• pp.15-20
• /
• 2008

Hydraulic analysis of water distribution system can be divided into demand-driven analysis and pressure-driven analysis. Demanddriven analysis can give unrealistic results to simulate hydraulic conditions under abnormal operating conditions such as sudden demand increase and pipe failure. In Korea, demand-driven analysis has been used to establish emergency water supply plan in many water projects, but it is necessary to use pressure-driven analysis for establishment of emergency water supply plan. In this study, WaterGEMS model that was developed for pressure-driven analysis is used to evaluation of emergency water supply plan of J city. As the results, it was able to draw up more efficient plan for water supply in small block, and established emergency water supply plan of J city was determined to be appropriate.

• 한국태양에너지학회:학술대회논문집
• /
• 2009.04a
• /
• pp.184-189
• /
• 2009

In order to improve the operation of energy systems, it is necessary for the urban communities to have reliable optimization routines, both computerized and manual, implemented in their organizations. However, before a production plan for the energy system units can be constructed, a prediction of the energy systems first needs to be determined. So, several methodologies have been proposed for energy demand prediction, but due to uncertainties in urban community, many of them will fail in practice. The main topic of this paper has been the development of a method for energy demand prediction at urban community. Energy demand prediction is important input parameters to plan for the energy planing. This paper presents a energy demand prediction method which estimates heat and electricity for various building categories. The method has been based on artificial neural networks(ANN). The advantage of ANN with respect to the other method is their ability of modeling a multivariable problem given by the complex relationships between the variables. Also, the ANN can extract the relationships among these variables by means of learning with training data. In this paper, the ANN have been applied in oder to correlate weather conditions, calendar data, schedules, etc. Space heating, cooling, hot water and HVAC electricity can be predicted using this method. This method can produce 10% of errors hourly load profile from individual building to urban community.