• Journal of Korea Port Economic Association
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• v.22 no.1
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• pp.175-198
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• 2006

This paper presents a network capacity model that can be used as an analytical tool for strategic planning and resource allocation for multimodal transportation systems. In the context of freight transportation, the multimodal network capacity problem (MNCP) is formulated as a mathematical model of nonlinear bi-level optimization problem. Given network configuration and freight demand for multiple origin-destination pairs, the MNCP model is designed to determine the maximum flow that the network can accommodate. To solve the MNCP, a heuristic solution algorithm is developed on the basis of a linear approximation method. A hypothetical exercise shows that the MNCP model and solution algorithm can be successfully implemented and applied to not only estimate the capacity of multimodal network, but also to identify the capacity gaps over all individual facilities in the network, including intermodal facilities. Transportation agencies and planners would benefit from the MNCP model in identifying investment priorities and thus developing sustainable transportation systems in a manner that considers all feasible modes as well as low-cost capacity improvements.

• Journal of KIBIM
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• v.6 no.3
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• pp.24-33
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• 2016

Planning occurs from day-to-day, small-scale decisions to large-scale infrastructure investment decisions. For that reason, various attempts have been made to appropriately assist decision-making process and its optimization. Lately, initiation of a large amount of data, also known as big data has received great attention from diverse disciplines because of versatility and adoptability in its use and possibility to generate new information. Accordingly, implementation of big data and other information management systems, such as geographic information systems (GIS) and building information modeling (BIM) have received enough attention to establish each of its own profession and other associated activities. In this extent, this study illustrates a series of big data implementation cases that can provide a lesson to urban planning domain. In specific, case studies analyze how data was used to extract the most optimized solution and what aspects could be helpful in relation to planning decisions. Also, important notions about GIS and its application in various urban cases are examined.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.47-58
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• 1988

The dynamic uncapacitated facility location model is formulated by a mixed integer programming. It has the objective of minimizing total discounted costs for meeting demands specified in different time periods at various demand centers. Costs include those for operation of facilities to demand centers and a fixed cost associated with the capital investment. The problem is decomposed into two simple Lagrangian relaxed subproblems which are coordinated by Lagrangian multipliers. We explored the effect of using the subgradient optimization procedure and a viable solution approach is proposed. Computational results are presented and further research directions are discussed.

• Proceedings of the KSR Conference
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• 2002.05a
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• pp.122-127
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• 2002

There are two methodologies to increase transport capacity of railway. The one is to invest railroad equipment or vehicles, and the other to improve operation efficiency through operation optimization. All of these is intended to increase transport capacity by improving line capacity. So far, we treat line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that change dynamically according to operational condition, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new line capacity estimation system based on the probability simulation and its applications.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.167-175
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• 2002

There are two methodologies to increase transport capacity of railway. One is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. All of these is intended to increase transport capacity by improving the line capacity. So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new estimation system of line capacity based on the probability simulation and its applications.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.668-673
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• 2003

Line Capacity is a criteria for transport capacity and is used to evaluate railroad investment alternatives or to decide train frequency when establish transportation plan. There are two methodologies to increase transport capacity of railway. One is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. Such all efforts are intended to increase transport capacity by improving line capacity. So far, this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. In this paper, we present a new estimation method of line capacity based on the probability simulation, and apply to normal railline section and special structured railine section.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.257-262
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• 2002

There are two methodologies to increase transport capacity of railway. The one is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. All of these is intended to increase transport capacity by improving line capacity So far, we treat line capacity as the criteria for evaluating investment alternatives or for restricting tram frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that change dynamically according to operational condition, so there is a need of new line capacity estimation system. The Purpose of this paper is to present a new line capacity estimation system based on the probability simulation and its applications.

• Proceedings of the KSR Conference
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• 2003.05a
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• pp.272-279
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• 2003

There are two methodologies to increase transport capacity of railway. One is to invest railroad equipment or vehicles, and the other is to improve operation efficiency through optimization. All of these is intended to increase transport capacity by improving the line capacity, So far, we treat the line capacity as the criteria for evaluating investment alternatives or for restricting train frequencies, and this criteria is calculated statical and experimental numerical formula. But, line capacity has special attribute that changes dynamically according to operational conditions, so there is a need of new line capacity estimation system. Korea Railroad Research Institute(KRRI) proposed a new line capacity estimation system based on the probability simulation method. In this research. we perform analysis of line capacity for the railway improvement alternatives, and to represent the results.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.918-922
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• 2009

The power expansion planning is large and capital intensive capacity planning. In the past, the expansion planning was established with the proper supply reliability in order to minimize social cost. However, the planning cannot use cost minimizing objective function in the power markets with many market participants. This paper proposed the power expansion planning process in the power markets. This system is composed of Regulator and GENCO's model. Regulator model used multi-criteria decision making rule. GENCO model is very complex problem. Thus, this system transacted the part by several scenario assuming GENCO model.

• Korean Management Science Review
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• v.30 no.3
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• pp.1-16
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• 2013

In this paper, we deal with an enhanced index fund strategy by implementing the exchange trade funds (ETFs) within the context of the Black-Litterman approach. The KOSPI200 index ETF is used to build risk-controlled portfolio that tracks the benchmark index, while the proposed Black-Litterman model mitigates estimation errors in incorporating both active investment views and equilibrium views. First, we construct a Black-Litterman model portfolio with the active market perspective based on the momentum strategy. Then, we update the portfolio with the KOSPI200 index ETF by using the equilibrium return ratio and weighted averages, while devising optimization modeling for improving the information ratio (IR) of the portfolio. Finally, we demonstrate the empirical viability of the proposed enhanced index strategies with KOSPI 200 data.