• 충청수학회지
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• 제26권1호
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• pp.85-90
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• 2013

We use the dynamic programming method to investigate the optimal consumption and investment problem with regime-switching. We derive the optimal solutions in closed-form with constant absolute risk aversion (CARA) utility.

• 대한건축학회논문집:구조계
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• 제35권3호
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• pp.43-48
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• 2019

Since the revision of the Rationalization of Energy Use Law, the spread of new and renewable energy in buildings has been promoted. In addition, the production of electric power and thermal energy is an important issue in the change of energy paradigm centered on the use of distributed energy. Among them, geothermal energy is attracting attention as a high-performance energy-saving technology capable of coping with heating / cooling and hot water load by utilizing the constant temperature zone of the earth. However, there is a disadvantage that the initial investment cost is high as a method of calculating the capacity of a geothermal facility by calculating the maximum load. The disadvantages of these disadvantages are that the geothermal energy supply is getting stagnant and the design of the geothermal system needs to be supplemented. In this study, optimization design of geothermal system was carried out using optimization tool. As a result of the optimization, the ground heat exchanger decreased by 30.8%, the capacity of the heat pump decreased by 7.7%, and the capacity of the heat storage tank decreased by about 40%. The simulation was performed by applying the optimized value to the program and confirmed that it corresponds to the load of the building. We also confirmed that all of the constraints used in the optimization design were satisfied. The initial investment cost of the optimized geothermal system is about 18.6% lower than the initial investment cost.

• 제어로봇시스템학회논문지
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• 제12권12호
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• pp.1169-1172
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• 2006

The prices of chemical products are fluctuated by several factors. The chemical companies can't predict and be ready to all of these changes, so they are exposed to the risk of a profit fluctuation. But they can reduce this risk by making a well-diversified product portfolio. This problem can be thought as the optimization of the product portfolio. We assume that the profits come from the 'spread' between a naphtha and a chemical product. We calculate a mean and a variation of each spread and develop an automatic module to calculate the optimal portion of each product. The theory is based on the Markowitz portfolio management. It maximizes the expected return while minimizing the volatility. At last we draw an investment selection curve to compare each alternative and to demonstrate the superiority. And we suggest that an investment selection curve can be a decision-making tool.

• 산경연구논집
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• 제13권1호
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• pp.23-32
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• 2022

Purpose: This study used ESG grade, but defined AESG, adjusted to the size of a company and examines whether it can be used as an investment strategy. Research design, data and methodology: The analysis sample in this study is a company that has given an ESG rating among companies listed on the Korea Stock Exchange. We examine the results through portfolio analysis and Fama-macbeth regression analysis. Results: As result of examining the long-only performance and the long-short performance by constructing quintile portfolios, it was observed that a significant positive return was shown. It was observed that there was an alpha that could not be explained in asset pricing models. Also, AESG had a return prediction effect in the result of a Fama-Macbeth regression that controlled corporate characteristic variables in individual stocks. Next, we confirmed AESG's usage through various portfolio composition. In the portfolio optimization, the Risk Efficient method was the most superior in terms of sharpe ratio and the construct multi-factor model with Value, Momentum and Low Vol showed statistically significant performance improvement. Conclusions: The results of this study suggest that it can be helpful in ESG investment to reflect the ESG rating of relatively small companies more through the scale adjustment of the ESG rating (i.e.AESG).

• 산업경영시스템학회지
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• 제46권4호
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• pp.63-73
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• 2023

This study explores modern portfolio theory by integrating the Black-Litterman portfolio with time-series clustering, specificially emphasizing K-shape clustering methodology. K-shape clustering enables grouping time-series data effectively, enhancing the ability to plan and manage investments in stock markets when combined with the Black-Litterman portfolio. Based on the patterns of stock markets, the objective is to understand the relationship between past market data and planning future investment strategies through backtesting. Additionally, by examining diverse learning and investment periods, it is identified optimal strategies to boost portfolio returns while efficiently managing associated risks. For comparative analysis, traditional Markowitz portfolio is also assessed in conjunction with clustering techniques utilizing K-Means and K-Means with Dynamic Time Warping. It is suggested that the combination of K-shape and the Black-Litterman model significantly enhances portfolio optimization in the stock market, providing valuable insights for making stable portfolio investment decisions. The achieved sharpe ratio of 0.722 indicates a significantly higher performance when compared to other benchmarks, underlining the effectiveness of the K-shape and Black-Litterman integration in portfolio optimization.

• 경영정보학연구
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• 제22권2호
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• pp.201-217
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• 2020

정보보호는 기업의 운영과 고객의 신뢰를 보장하는 필수요소이며 침해사고 예방을 통해 불확실한 피해를 완화시킬 수 있기 때문에 적절한 정보보호 대책의 선택과 적정투자 수준을 결정하는 것이 중요하다. 본 연구는 다양한 산업군에 속해있는 기업에서 정보보호 대책 투자에 활용할 수 있는 예산 범위에서 구성할 수 있는 최적의 정보보호 대책 포트폴리오 구성뿐만 아니라, 각 대책의 적절한 투자 수준에 대한 의사결정 지원 모델을 제시한다. 이를 위하여 산업군별 침해사고 유형 통계를 분석하고 유전자 알고리즘을 활용하여 최적 정보보호 대책 투자 포트폴리오를 도출한다. 도출된 모델을 기존 유전자 알고리즘을 이용한 정보보호 대책 투자 최적화 모델과 비교하고 기업 대상 설문 조사를 통하여 실제 사례를 분석한다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.145-145
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• 2021

Water distribution networks (WDNs) are designed to satisfy water requirement of an urban community. One of the central issues in human history is providing sufficient quality and quantity of water through WDNs. A WDN consists of a great number of pipelines with different ages, lengths, materials, and sizes in varying degrees of deterioration. The available annual budget for rehabilitation of these infrastructures only covers part of the network; thus it is important to manage the limited budget in the most cost-effective manner. In this study, a novel pipe replacement scheduling approach is proposed in order to smooth the annual investment time series based on a life cycle cost assessment. The proposed approach is applied to a real WDN currently operating in South Korea. The proposed scheduling plan considers both the annual budget limitation and the optimum investment on pipes' useful life. A non-dominated sorting genetic algorithm is used to solve a multi-objective optimization problem. Three decision-making objectives, including the minimum imposed LCC of the network, the minimum standard deviation of annual cost, and the minimum average age of the network, are considered to find optimal pipe replacement planning over long-term time period. The results indicate that the proposed scheduling structure provides efficient and cost-effective rehabilitation management of water network with consistent annual budget.

• International Journal of Quality Innovation
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• 제8권2호
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• pp.20-31
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• 2007

Moral hazard and adverse selection often exist in asymmetric information environment. In this paper, quality investment decision problem is studied under moral hazard. A basic model for quality investment level decision is developed with the supplier as a principal and the buyer as an agent. And then we regard the supplier and the buyer's rational limitations to set up a model when the buyer's quality evaluation and processing activities are hidden. The model is optimized and the results under different backgrounds are discussed and compared. Results show that the buyer's quality evaluation level and processing level are mostly influenced by the supplier's quality assurance payment. Both the supplier and the buyer choose different quality investment levels under moral hazard because of the supplier's payment to the buyer in case of internal failure and external failure.

• 대한전기학회논문지:전력기술부문A
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• 제49권2호
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• pp.56-61
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• 2000

In the paper, the system loss sensitivity index that implies the incremental system loss with respect to the change of bus power is derived using optimization technique. The index λ reaches $\infty$ at critical loading point and can be applied to actual power systems for following purposes. 1) Evaluation of system voltage stability 2)Optimal investment of reactive power focused on minimizing system loss and maximizing system voltage stability 3)Optimal re-location of reactive power focused on minimizing system loss and maximizing system voltage stability 4)Optimal load shedding in case of severe system contingency focused on minimizing system loss and maximizing system voltage stability. Case studies for each application have proved their effectiveness.

• 산업경영시스템학회지
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• 제43권4호
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• pp.229-235
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• 2020

Investors aim to maximize the return rate for their own investment, utilizing various information as possible as they can access. However those investors, especially individual investors, have limitations of interpretation of the domain-specific information or even the acquisition of the information itself. Thus, individual investors tend to make decision affectively and frequently, which may cause a loss in returns. This study aims to analyze analysts' target price and to suggest the strategy that could maximize individual's return rate. Most previous literature revealed that the optimistic bias exists in the analysts' target price and it is also confirmed in this study. In this context, this study suggests the upper limit of target rate of returns and the optimal value named 'alpha(α)' which performs the adjustment of proposed target rate to maximize excess earning returns eventually. To achieve this goal, this study developed an optimization problem using linear programming. Specifically, when the analysts' proposed target rate exceeds 30%, it could be adjusted to the extent of 59% of its own target rate. As apply this strategy, the investors could achieve 1.2% of excess earning rate on average. The result of this study has significance in that the individual investors could utilize analysts' target price practically.