• Korean System Dynamics Review
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• v.4 no.1
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• pp.33-53
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• 2003

How to maintain the optimal electric power generation mix is one of the important problems in electric power industry. The objective of this study is to develop a computer model which can be used to forecast the investment in power generation unit by the plant owners after restructuring of electric power industry. Restructuring of electric power industry will make difference in decision making process of investment in power generation unit. After Privatiazation of Power Industry, Gencos will think that profit is the most important factor among all others attracting the investment in the industry. Coal power generation is better than LNG CCGT in terms of profit. However, many studies show that LNG CCGT will be main electric power generation source because the rest of factors other than profit in LNG CCGT are superior than Coal power generation. Because the nst of factors other than profit in LNG CCGT are superior than Coal power generation. The impacts of the various government policies can be analyzed using the computer model, thus the government can formulate effective policies for achieving the desired electric power generation mix.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.369-374
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• 2008

This paper presents the evaluation procedures and the estimation method for the estimation of optimal rebate level for EE(Energy Efficiency) programs. The penetration amount of each appliance is estimated by applying price function to preferred diffusion model resulted from model compatibility test. To estimate the optimal rebate level, two objective functions which express the maximum energy saving and operation benefit are introduced and by multi-objective function which can simultaneously consider two objective functions the optimal rebate level of each appliance is estimated. And then, using the decided rebate level and each penetration amount, the priority order for reasonable investment of each high-efficiency appliance is estimated compared to the results of conventional method. Finally, using a benefit/cost analysis based on California standard practice manual, the economic analysis is implemented for the four perspectives such as participant, ratepayer impact measure, program administrator cost and total resource cost.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.3
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• pp.49-64
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• 2000

A vendor supplies a product to a sole/major buyer on a lot-for-lot basis under deterministic inventory control conditions. The basic premise is that the setup cost reduction technologies are available to both the buyer and the vendor, and that the vendor's inventory and setup reduction investment costs differ from the buyer's. Therefore, an individually designed ordering and setup cost reduction policy will likely cause mismatches between the vendor's and the buyer's optimal cycle times. For this situation, we show that a joint optimal setup cost reduction and ordering policy, together with an appropriate side payment(quantity discount or premium price) schedule, can be designed in a spirit in a spirit of coordination to eliminate mismatches in individual optimal cycle times.

• Korean Management Science Review
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• v.30 no.1
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• pp.167-181
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• 2013

We investigate the dynamic asset allocation problem under inflation risk when the wealth of an investor is constrained with minimum requirements. To capture the investor's risk preference, the CRRA utility function is considered and he maximizes his expected utility at predetermined date of the refund by participation in the financial market. The financial market is supposed to consist of three kinds of financial instruments which are a risk free asset, a risky asset, and an index bond. The role of an index bond is managing inflation risk represented by price process. The optimal wealth and the optimal asset allocation are derived explicitly by using the method to get the European call option pricing formula. From the numerical results, it is confirmed that the investments on index bond is high when the investor's wealth level is low. However, as his wealth increases, the investments on index bond decreases and he invests on risky asset more. Furthermore, the minimum wealth constraint induces lower investment on risky asset but the effect of the constraints is reduced as the wealth level increases.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.44 no.1
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• pp.21-24
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• 1995

The larger and the more complicated the system size and configuration grow, the more serious the system loss problem becomes. Exessive system loss causes severs system voltage depression, which even may result in system voltage collapse. This paper proposes an effective tool for minimizing the system power loss by optimal re-location of the static condenser based on the system loss sensitivity index .lambda.$_{Q}$. It is possible to determine the optimal location and amount of VAR investment for minimizing the system loss by priority of .lambda.$_{Q}$ index given for each bus. Several computational techniques for avoiding divergency of the load flow solution are proposed. The loss sensitivity index .lambda.$_{Q}$ uses information of normal power flow equations and their Jacobians. Two case studies proved the effectiveness of the algorithm proposed.posed.

• IE interfaces
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• v.13 no.2
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• pp.217-224
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• 2000

This paper analyzes the effects of setup cost reduction in a dynamic lot-sizing model for a single-facility multi-product problem. In the model, demands for each product are known, no backlogging is allowed, and a single resource is employed. Also, setup cost is defined as a function of capital expenditure to invest in setup cost reduction. Furthermore, in each production period the facility (or plant) produces many products, each representing a fixed part of the involved production activity (or input resource quantity). In this paper, the structure of the optimal solution is characterized and an efficient algorithm is proposed for simultaneously determining the optimal lot size with reduced setup cost and the optimal investment in setup cost reduction. Also, the proposed algorithm is illustrated by a numerical example with a linear and an exponential setup reduction functions.

• Proceedings of the KIEE Conference
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• 1998.11a
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• pp.298-300
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• 1998

The superconducting magnetic energy storage (SMES) system which has characteristics of high efficiency and rapid response is a way to maximize a utility's generation and transmission capacity. But SMES is required for much capital and operating cost. Therefore, It is important to determine the optimal size of SMES for constructing and operating. In this paper, we proposed a method of determinating an optimal size of a large scale of SMES for energy storage and a small scale of SMES for stabilizing power system.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.377-396
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• 2023

As the cryptocurrency market continues to grow, it has developed into a new financial market. The need for investment strategy research on the cryptocurrency market is also emerging. This study aims to conduct an empirical analysis on an investment methodology of cryptocurrency that combines short-term trading strategy and deep learning. Daily price data of the Ethereum was collected through the API of Upbit, the Korean cryptocurrency exchange. The investment performance of the experimental model was analyzed by finding the optimal parameters based on past data. The experimental model is a volatility breakout strategy(VBS), a Long Short Term Memory(LSTM) model, moving average cross strategy and a combined model. VBS is a short-term trading strategy that buys when volatility rises significantly on a daily basis and sells at the closing price of the day. LSTM is suitable for time series data among deep learning models, and the predicted closing price obtained through the prediction model was applied to the simple trading rule. The moving average cross strategy determines whether to buy or sell when the moving average crosses. The combined model is a trading rule made by using derived variables of the VBS and LSTM model using AND/OR for the buy conditions. The result shows that combined model is better investment performance than the single model. This study has academic significance in that it goes beyond simple deep learning-based cryptocurrency price prediction and improves investment performance by combining deep learning and short-term trading strategies, and has practical significance in that it shows the applicability in actual investment.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.956-962
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• 2005

This paper presents an integrated analysis of production and financing decisions. We assume that a cash storage unit is installed to manage the cash flows related with production activities such as raw material procurement, process operating setup, Inventory holding cost and finished product sales. Temporarily financial investments are allowed for more profit. The production plant is modeled by the Batch-Storage Network with Recycle Streams in Yi and Reklaitis (2003). The objective function of the optimization is minimizing the opportunity costs of annualized capital investment and cash/material inventory while maximizing stockholder's benefit. No depletion of all the material and cash storage units is major constraints of the optimization. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the cash and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems and analytical lot sizing equations under a mild assumption about the cash flow pattern of stockholder's dividend. The first subproblem is a separable concave minimization network flow problem whose solution yields the average material flow rates through the networks. The second subproblem determines the decisions about financial Investment. Finally, production and financial transaction lot sizes and startup times can be determined by analytical expressions as far as the average flow rates are calculated. The optimal production lot and storage sizes considering financial factors are smaller than those without such consideration. An illustrative example is presented to demonstrate the results obtainable using this approach.

• Informatization Policy
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• v.19 no.2
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• pp.85-105
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• 2012

So far, the importance of informatization, as well as investment into it, has been growing steadily. Due to the uncertainties and risks in adopting information technologies, systematic decision-making is definitely needed in investing in a large scale information system. Based on the existing theories about the economic life span of information systems and in consideration of the actual cost involved in the adoption and operation of the systems by the financial institutions in Korea, this study presents the optimal economic life span for all types of information systems in terms of the economic cost and generalizes the optimal life span. The ultimate purpose of this study is to develop a model that could be used in anticipating the timing of economic replacement of the information system of the same type and making decisions on IT investment.