• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.580-587
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• 2017

Recently, as the education population of Korea has been rapidly declining, many changes have been taking place in the university environment. Especially, community colleges linked to local communities have responded to these crises through various educational changes, such as three-year study transfers, work-parallelism, and employee commissioned education. However, such changes in the contents of education are causing a new type of classroom allocation problem, in which it is difficult to assign the limited number of classrooms to the major courses. In this paper, we classified the constraints involved in assigning classrooms into absolute constraints and relative constraints, mathematically modeled them, and allocated the classrooms optimally through optimization software. The results were satisfactory and enabled us to obtain superior results in terms of the various performance indices (classroom utilization rate, teacher satisfaction, etc.) than when assigning classrooms in the normal way.

• Journal of the Korean School Mathematics Society
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• v.22 no.3
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• pp.257-275
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• 2019

Technology-based convergence education is being emphasized for students in the era of the fourth industrial revolution. In math education, students need to increase their capabilities in the future by having them experience mathematical problems using robots and sensors, a key technology in the era of the fourth industrial revolution. To this end, it is necessary to present educational uses for educational robots in relation to math and curriculum from a 'mathematics education perspective' and analyze its educational use in relation to the mathematics and curriculum, considering the role of mathematics at the base of the process of exploring real-world phenomena and solving problems. Based on the analysis of Van Hiele levels of development in geometry and the LOGO activity level of Olson et al.(1987), this study analyzed and presented the level of LEGO Mindstorm activity, a representative educational Robot capable of collecting and analyzing data and programming in the form of block language, in the first to fourth level.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.3
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• pp.218-224
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• 2011

A modal method is presented for the investigation of the effects of measurement errors in damage detection for dynamic structural systems. The structural modifications to the baseline system result in the response changes of the perturbed structure, which are measured to determine a unique system in the inverse problem of damage detection. If the numerical modal data are exact, mathematical programming techniques can be applied to obtain the accurate structural changes. In practice, however, the associated measurement errors are unavoidable, to some extent, and cause significant deviations from the correct perturbed system because of the intrinsic instability of eigenvalue problem. Hence, a self-equilibrating inverse system is allowed to drift in the close neighborhood of the measured data. A numerical example shows that iterative procedures can be used to search for the damaged structural elements. A small set of selected degrees of freedom is employed for practical applicability and computational efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.1-17
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• 2015

In this paper, we propose a portfolio selection model utilizing a Markov chain for investing in the foreign exchange market based on market forecasts and exchange rate movement predictions. The proposed model is utilized to compute optimum investment portfolio weights for investing in margin-based markets such as the FX margin market. We further present an objective investment algorithm for applying the proposed model in real-life investments. Empirical performance of the proposed model and investment algorithm is evaluated by conducting an experiment in the FX market consisting of the 7 most traded currency pairs, for a period of 9 years, from the beginning of 2005 to the end of 2013. We compare performance with 1) the Dollar Index, 2) a 1/N Portfolio that invests the equal amount in the N target assets, and 3) the Barclay BTOP FX Index. Performance is compared in terms of cumulated returns and Sharpe ratios. The results suggest that the proposed model outperforms all benchmarks during the period of our experiment, for both performance measures. Even when compared in terms of pre- and post-financial crisis, the proposed model outperformed all other benchmarks, showing that the model based on objective data and mathematical optimization achieves superior performance empirically.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.83-95
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• 2014

In this paper, we develop a portfolio selection model that can be used to invest in markets with margin requirements such as the foreign exchange market. An investment algorithm to implement the proposed portfolio selection model based on objective historical data is also presented. We further conduct empirical analysis on the performance of a hypothetical investment in the foreign exchange market, using the proposed portfolio selection model and investment algorithm. Using 7 currency pairs that recorded the highest trading volume in the foreign exchange market during the most recent 10 years, we compare the performance of 1) the Dollar Index, 2) a 1/N Portfolio which equally allocates capital to all N assets considered for investment, and 3) a hypothetical investment portfolio selected and managed according to the portfolio selection model and investment algorithm proposed in this paper. Performance is compared in terms of accumulated returns and Sharpe ratios for the 10-year period from January 2003 to December 2012. The results show that the hypothetical investment portfolio outperforms both benchmarks, with superior performance especially during the period following financial crisis. Overall, this paper suggests that a mathematical approach for selecting and managing an optimal investment portfolio based on objective data can achieve outstanding performance in the foreign exchange market.

• Korean Management Science Review
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• v.30 no.1
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• pp.73-89
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• 2013

This paper develops an investment algorithm based on Markowitz's Portfolio Selection Theory, using historical stock return data, and empirically evaluates the performance of the proposed algorithm in the U.S. and the Hong Kong stock markets. The proposed investment algorithm is empirically tested with the 30 constituents of Dow Jones Industrial Average in the U.S. stock market, and the 30 constituents of Hang Seng Index in the Hong Kong stock market. During the 6-year investment period, starting on the first trading day of 2006 and ending on the last trading day of 2011, growth rates of 12.63% and 23.25% were observed for Dow Jones Industrial Average and Hang Seng Index, respectively, while the proposed investment algorithm achieved substantially higher cumulative returns of 35.7% in the U.S. stock market, and 150.62% in the Hong Kong stock market. When compared in terms of Sharpe ratio, Dow Jones Industrial Average and Hang Seng Index achieved 0.075 and 0.155 each, while the proposed investment algorithm showed superior performance, achieving 0.363 and 1.074 in the U.S. and Hong Kong stock markets, respectively. Further, performance in the U.S. stock market is shown to be less sensitive to an investor's risk preference, while aggressive performance goals are shown to achieve relatively higher performance in the Hong Kong stock market. In conclusion, this paper empirically demonstrates that an investment based on a mathematical model using objective historical stock return data for constructing optimal portfolios achieves outstanding performance, in terms of both cumulative returns and Sharpe ratios.

• The Journal of Information Systems
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• v.29 no.1
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.105-111
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• 2017

Vendor Managed Inventory is a well-known vendor-retailer coordination approach in supply chain management where the vendor manages inventory of the retailer and determines the order interval and order quantity for the retailer. To consider practical situation, the upper limit of inventory for the retailer is set. If the inventory level for the retailer exceeds the upper limit, then the penalty cost is charged to the retailer. Furthermore, maximum allowable inventory level is set for the vendor to prevent the vendor from keeping much inventory. Single-vendor multi-retailer supply chain model with upper limit of inventory for vendor and retailers is studied. All the retailers' are assumed to have the common cycle time, and a vendor manages retailers' inventory and replenishes products. The mathematical formulation is introduced to minimize the total cost including the penalty cost violating the upper limit of inventory for retailers with the constraint of maximum allowable inventory level. The solution procedure based on Karush-Kuhn-Tucker (KKT) conditions is derived. KKT conditions are often applied to find an optimal solution of nonlinear programming problem with constraints. An illustrative example is used to show the application of the proposed solution procedure. Furthermore, sensitivity analysis is done to find out the relationship between maximum allowable inventory level and other values such as order quantity, the number of shipment, vendor's cost, retailer's cost, and total cost. As maximum allowable inventory level decreases, the number of shipment decreases but total cost increases. Order quantity has the trend of decline and is affected by the number of shipment.

• IE interfaces
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• v.20 no.1
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• pp.1-10
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• 2007

The main purpose of this research is to find out whether curriculums of industrial engineering (IE) departments meet the demand of IE graduates working in various fields. The research was conducted as an online questionnaire survey selecting IE Graduates working in industries as practising engineers. 1,324 participants were validated among 1,477 participants. 13 fields were selected and used in the survey. Those were; 1) Mathematical statistics, 2) Computer, 3) Purchase, 4) Production system, 5) Logistics, 6) Marketing, 7) Monetary, 8) Experiment methods, 9) Operations Research (OR), 10) Human Factors, 11) Quality, 12) Engineering management, and 13) Information systems. Using the 5-scale Likert rating, each education subject was assessed both in terms of its usefulness in practices and the amount it being taught in school. As a result, courses such as motion/time study, linear programming that IE has traditionally focused showed less usefulness in practices while it is taught in relatively large amount in schools. However, courses such as 6 sigma, CRM which are closely related to industrial practices showed high usefulness in practices compared with low degree of teaching in school. This was the first ever large scalesurvey conducted for IE graduates in Korea. The result of survey displayed many helpful information on current status and future direction of IE education in Korea.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.1 s.71
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• pp.63-71
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• 2006

This study presents the effective stiffness-based optimal technique to control Quantitatively lateral drift for shear wall-frame structure system using sensitivity analysis. To this end, the element stiffness matrices are constituted to solve the compatibility problem of displacement degree of freedom between the frame and shear wall. Also, lateral drift constraint to introduce the approximation concept that can preserve the generality of the mathematical programming and can effectively solve the large scaled problems is established. And, the section property relationships for shear wall and frame members are considered in order to reduce the number of design variables and differentiate easily the stiffness matrices. Specifically, constant-shape assumption which is uniformly varying in size during optimal process is applied in frame structure. The thickness or length of shear wall can be changed depending on user's intent. Two types of 20 story shear wall-frame structure system are presented to illustrate the features of the stiffness-based optimal design technique.