• Title/Summary/Keyword: Optimization of Investment

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A Study on Dynamic Optimization of Time-Of-Use Electricity Rates (계절.시간대별 차등 전기요금의 동태적 최적화에 관한 연구)

  • 김동현;최기련
    • Journal of Energy Engineering
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    • v.5 no.1
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    • pp.87-92
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    • 1996
  • This paper formulates dynamic optimization model for Time-Of-Use Rates when a electric power system consists of three generators and a rating period is divided into three sub-periods. We use Pontryagin's Maximum Principle to derive optimal price and investment policy. Particularly the cross-price elasticities of demand are considered in the objective function. We get the following results. First, the price is equal to short-run marginal cost when the capacity is sufficient. However, if the capacity constraint is active, the capacity cost is included in the price. Therefore it is equal to the long-run marginal cost. Second, The length of rating period affects allocation of capacity cost for each price. Third, the capacity investment in dynamic optimization is proportional to the demand growth rate of electricity. However the scale of investment is affected by not only its own demand growth rate but also that of other rating period.

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Optimization Model for Sewer Rehabilitation Using Fast Messy Genetic Algorithm (fmGA를 이용한 하수관거정비 최적화 모델)

  • Ryu, Jae-Na;Ki, Beom-Joon;Rark, Kyoc-Hong;Lee, Cha-Don
    • Journal of Korean Society of Water and Wastewater
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    • v.18 no.2
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    • pp.145-154
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    • 2004
  • A long-term sewer rehabilitation project consuming an enormous budget needs to be conducted systematically using an optimization skill. The optimal budgeting and ordering of priority for sewer rehabilitation projects are very important with respect to the effectiveness of investment. In this study, the sewer rehabilitation optimization model using fast-messy genetic algorithm is developed to suggest a schedule for optimal sewer rehabilitation in a subcatchment area by modifying the existing GOOSER$^{(R)}$ model having been developed using simple genetic algorithm. The sewer rehabilitation optimization model using fast-messy genetic algorithm can improve the speed converging to the optimal solution relative to GOOSER$^{(R)}$, suggesting that it is more advantageous to the sewer rehabilitation in a larger-scale subcatchment area than GOOSER.

Stock Investment of Agriculture Companies in the Vietnam Stock Exchange Market: An AHP Integrated with GRA-TOPSIS-MOORA Approaches

  • NGUYEN, Phi-Hung;TSAI, Jung-Fa;KUMAR G, Venkata Ajay;HU, Yi-Chung
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.7
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    • pp.113-121
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    • 2020
  • Multi-criteria stock selection is a critical issue for effective investment since the improper stock investment might cause many problems affecting investors negatively. Investors need a range of financial indicators while they are choosing the optimal set of stocks to invest. This study aims to rank the stock of agriculture companies indexed on the Vietnam Stock Exchange Market. The data of 13 agriculture companies during the 2016-2019 periods was analyzed by analytical hierarchy process (AHP) integrated with grey relational analysis (GRA), multi-objective optimization ratio analysis (MOORA), and technique for order performance by similarity to ideal solution (TOPSIS). The AHP method is employed to determine the weights of the proposed financial ratios, and GRA, TOPSIS, and MOORA approaches are used to obtain final ranking. The results indicated that HSL is the top stock with the highest rank and GRA, MOORA, and TOPSIS rankings have strong correlation values between 0.78-1. The findings suggest that the integrated model could be implemented effectively to specific analysis of industries such as oil and gas, textiles, food, and electronics in future research. Further, other techniques like COPRAS, KEMIRA, and EDAS could be employed to evaluate the financial performance of other companies to solve investment problems.

An Empirical Study on the Export and Import Effects of Foreign Direct Investment on the Blue Economic Zone of the Shandong Peninsula in China

  • Lee, Sung-Joon;Zhai, Shuai
    • Journal of Distribution Science
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    • v.11 no.1
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    • pp.15-23
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    • 2013
  • Purpose - During a reform period lasting 30 years, the Blue Economic Zone (BEZ) in the Shandong Peninsula has made progress in attracting foreign investment, and has acquired the foreign direct investment (FDI) essential for economic growth. It is therefore important to conduct a proactive and systematic study of FDI in the BEZ. Research design, data, methodology - This dissertation discusses the contribution of FDI on economic growth, from both a theoretical and empirical perspective. Taking seven core cities for study, statistics and econometrics are used, and panel data are used to validate FDI contribution to import and export in the BEZ. Results- FDI was found to exert both positive and negative influences on the imports and exports of the BEZ. In other words, the research findings are consistent with Trade Generated and Inverse Trade Generated theories put forward by Kojima and Mundell, among other researchers mentioned earlier in this paper. Further, FDI has greatly increased imports and exports for the BEZ. Conclusions - According to the results of this empirical study on local investment environment optimization, FDI plays an important role in foreign trade. This dissertation puts forward recommendations on using FDI to better promote economic growth in the BEZ.

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OPTIMAL CONSUMPTION/INVESTMENT AND LIFE INSURANCE WITH REGIME-SWITCHING FINANCIAL MARKET PARAMETERS

  • LEE, SANG IL;SHIM, GYOOCHEOL
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.19 no.4
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    • pp.429-441
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    • 2015
  • We study optimal consumption/investment and life insurance purchase rules for a wage earner with mortality risk under regime-switching financial market conditions, in a continuous time-horizon. We apply the Markov chain approximation method and suggest an efficient algorithm using parallel computing to solve the simultaneous Hamilton-Jaccobi-Bellman equations arising from the optimization problem. We provide numerical results under the utility functions of the constant relative risk aversion type, with which we illustrate the effects of regime switching on the optimal policies by comparing them with those in the absence of regime switching.

An Optimization Model for Resolving Circular Shareholdings of Korean Large Business Groups (대규모 기업집단의 순환출자 해소를 위한 최적화 모형)

  • Park, Chan-Kyoo;Kim, Dae-Lyong
    • Journal of the Korean Operations Research and Management Science Society
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    • v.34 no.4
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    • pp.73-89
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    • 2009
  • Circular shareholdings among three companies are formed when company A owns stock in company B, company B owns stock in company C, and company C owns stock in company A. Since circular shareholdings among large family-controlled firms are used to give the controlling shareholder greater control or more opportunities to expropriate minority investors, the government has encouraged large business groups to gradually remove their circular shareholdings. In this paper, we propose a combinatorial optimization model that can answer the question, which equity investments among complicated investment relationships of one large business group should be removed to resolve its circular shareholdings. To the best knowledge of the authors, our research is the first one that has approached the circular shareholding problem in respect of management science. The proposed combinatorial optimization model are formulated into integer programming problem and applied to some Korean major business groups.

The Investment Scheme of the Maintenance Planning with Limited Investment Budget in the Distribution Systems for Minimizing the Interruption Cost (제한된 투자 예산으로 정전비용 최소화를 위한 배전계통 유지보수 계획의 투자 방안)

  • Hwang, Won-Il;Kim, Kyu-Ho;Kim, Hong-Rae;Song, Kyung-Bin
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.24 no.8
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    • pp.1-7
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    • 2010
  • The reliability of a power system has close relationship with the maintenance of the distribution systems. This paper presents the method of the maintenance planning of the distribution systems by minimizing the interruption cost. The interruption cost for the equipment failures is formulated using time varying failure rate and minimized by optimization of the object function. The proposed method provides the priority list for the investment of the maintenance subject to the limited investment budget by the economic analysis. In order to test the proposed method, the modified distribution system of a rural area is introduced for the testing system. Test results show that the proposed method is good enough by evaluating the improvement of the reliability of the power system.

A Study on DRL-based Efficient Asset Allocation Model for Economic Cycle-based Portfolio Optimization (심층강화학습 기반의 경기순환 주기별 효율적 자산 배분 모델 연구)

  • JUNG, NAK HYUN;Taeyeon Oh;Kim, Kang Hee
    • Journal of Korean Society for Quality Management
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    • v.51 no.4
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    • pp.573-588
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    • 2023
  • Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

A Model for Supporting Information Security Investment Decision-Making Considering the Efficacy of Countermeasures (정보보호 대책의 효과성을 고려한 정보보호 투자 의사결정 지원 모형)

  • Byeongjo Park;Tae-Sung Kim
    • Information Systems Review
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    • v.25 no.4
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    • pp.27-45
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    • 2023
  • The importance of information security has grown alongside the development of information and communication technology. However, companies struggle to select suitable countermeasures within their limited budgets. Sönmez and Kılıç (2021) proposed a model using AHP and mixed integer programming to determine the optimal investment combination for mitigating information security breaches. However, their model had limitations: 1) a lack of objective measurement for countermeasure efficacy against security threats, 2) unrealistic scenarios where risk reduction surpassed pre-investment levels, and 3) cost duplication when using a single countermeasure for multiple threats. This paper enhances the model by objectively quantifying countermeasure efficacy using the beta probability distribution. It also resolves unrealistic scenarios and the issue of duplicating investments for a single countermeasure. An empirical analysis was conducted on domestic SMEs to determine investment budgets and risk levels. The improved model outperformed Sönmez and Kılıç's (2021) optimization model. By employing the proposed effectiveness measurement approach, difficulty to evaluate countermeasures can be quantified. Utilizing the improved optimization model allows for deriving an optimal investment portfolio for each countermeasure within a fixed budget, considering information security costs, quantities, and effectiveness. This aids in securing the information security budget and effectively addressing information security threats.