• The Korean Journal of Ecology
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• v.19 no.1
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• pp.9-19
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• 1996

The model PINUSCO2 hased of physiology was creted to simulate carbon dioxide budget in a population of red pine(pinus densiflora) which is one of the dominant species in Korea. Driving forces of PINUSCO2 are global radiation, maximum and minimum air temperatures. State variables fo the model are standing crops of leaf, branch, trunk and root of the red pine population. PINUSCO2 calculates net photosynthesis of canopy and respiration of each organ with 1 hour time step. PINUSCO2 estimated the annual gross productivity, respiration and net productivity of the red pine population as 43.99, 24.55, and 19.44 ton CO2·ha-1·yr-1, respectively, at the study sity(35°58′00"N, 128°25′35"E). PINUSCO2 showed that the red pine population grew mainly in spring and fall, and that in summer daily net population productivity frequently became negative.

• 전기의세계
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• v.21 no.3
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• pp.48-52
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• 1972

The application of pontryagin's Maximum Principle to the optimal control eventually leads to the problem of solving the two point boundary value problem. Most of problems have been related to their own special factors, therfore it is very hard to recommend the best method of deriving their optimal solution among various methods, such as iterative Runge Kutta, analog computer, gradient method, finite difference and successive approximation by piece-wise linearization. The gradient method has been applied to the optimal control of two point boundary value problem in the power systems. The most important thing is to set up some objective function of which the initial value is the function of terminal point. The next procedure is to find out any global minimum value from the objective function which is approaching the zero by means of gradient projection. The algorithm required for this approach in the relevant differential equations by use of the Runge Kutta Method for the computation has been established. The usefulness of this approach is also verified by solving some examples in the paper.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.4
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• pp.53-58
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• 2003

Design of the corrugated watertight bulkhead for a bulk carrier is principally determined by the permissible limit of Classification requirements. As the weight of upper and lower stool has considerable portion of the total weight of the transverse bulkhead, optimum design including the stool geometry and size will play an important role on economic shipbuilding. The purpose of this study is focused on the minimization of steel weight using the design variables, which are the shape and the size of the corrugation as well as the upper and lower stools. Discrete variables are used as design variables for the practical design. In this study, the evolution strategies (ES), which can highly improve the possibility of leaching the global minimum point, are selected as an optimization method. Usefulness of this study is verified by comparison with the proven type ship design. As objective function, total weight of the transverse bulkhead including the upper and lower stools is used.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.740-749
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• 1998

This paper proposes compression of image data using neural networks based on conjugate gradient method and dynamic tunneling system. The conjugate gradient method is applied for high speed optimization .The dynamic tunneling algorithms, which is the deterministic method with tunneling phenomenon, is applied for global optimization. Converging to the local minima by using the conjugate gradient method, the new initial point for escaping the local minima is estimated by dynamic tunneling system. The proposed method has been applied the image data compression of 12 ${\times}$12 pixels. The simulation results shows the proposed networks has better learning performance , in comparison with that using the conventional BP as learning algorithm.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.333-336
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• 1991

In this paper, Hopfield & Tank model-like artificial neural network structure is proposed, which can be used for the optimal path planning problems such as the unit commitment problems or the maintenance scheduling problems which have been solved by the dynamic programming method or the branch and bound method. To construct the structure of the neural network, an energy function is defined, of which the global minimum means the optimal path of the problem. To avoid falling into one of the local minima during the optimization process, the simulated annealing method is applied via making the slope of the sigmoid transfer functions steeper gradually while the process progresses. As a result, computer(IBM 386-AT 34MHz) simulations can finish the optimal unit commitment problem with 10 power units and 24 hour periods (1 hour factor) in 5 minites. Furthermore, if the full parallel neural network hardware is contructed, the optimization time will be reduced remarkably.

• Korean Management Science Review
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• v.28 no.2
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• pp.1-16
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• 2011

In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.689-697
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• 2005

The soil nailing system at permanent slope reinforcement is used with various facing methods in Korea. Also, pressure-injected grout technique is variously applied to many structures. However, most design of the pressure-injected grout technique have been carried out empirically because of complicated mechanisms associated with the behavior of surrounding soils and the hardening process of cement grout. Therefore this study, a newly modified soil nailing technology named as the PGSN (Pressure Grouting Soil Nailing) system with fabric form is developed to increase the global stability. Up to now, the PGSN system has been estimated mainly focusing on an establishment of the design procedure. In the present study, numerical study are carried out to evaluate potential failure surface and minimum factor of safety including facing stiffness and expanded radius of cemented grout by SSR (Shear Strength Reduction) technique. Also, results of numerical analysis are carried out for the typical section of soil nails slope using $FLAC^{2D}$ program for expanded effective radius by pressure grouting.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.217-228
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• 1994

This paper presents a new integer formulation (Type III ALB) for a single model assembly line balancing problem. The objective of the formulation is to minimize the total idle time, which is defined as the product of the number of work stations and the cycle times minus the total work content. This formulation considers currently existing Type I (minimizing the number of work stations for a given cycle time) and type II (minimizing the cycle time for a given number of work stations) formulations as its special cases and provides the global minimum solutions of the cycle time and the number of work stations. This information would be of great value to line designers involved in designing new assembly lines and rebalancing old lines under flexible conditions. Solution methods based on combination of Type I and Type II approaches are also suggested and compared.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.61-64
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• 2002

We constructed climagraphs for 16 regions of Korea by using the average monthly minimum air temperature, maximum air temperature and global radiation. We characterized the outside climate requirements corresponding to the climate requirements of crops in greenhouses. The climagraphs allow to decide the appropriate climate periods for greenhouse cultivation without heating and cooling equipment. These graphs may be used for analyzing climatic characteristic of a given area, selecting the suitable region and greenhouse and making a rational plan for greenhouse cropping in Korea. We found difficulty in deciding the beginning and end of greenhouse heating and cooling period due to insufficient references.

• IE interfaces
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• v.11 no.3
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• pp.115-128
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• 1998

This paper presents a development of operation scheduling and reactive operation scheduling system for hull fabrication. The methodology for implementing operation scheduling system is HHGA(Hierarchical Hybrid Genetic Algorithm) which exploits both the global perspective of the genetic algorithm and the rapid convergence of the heuristic search for operation scheduling. The methodology for the reactive operation scheduling is the revised HHGA which consists of manual schedule editor for occurrence of exceptional events and the revised scheduling method used in operation scheduling. As the results of experiment, it has been confirmed that HHGA is able to search good operation scheduling within reasonable time, and the revised HHGA is able to search load-balanced reactive operation scheduling with minimum changes of initial operation schedule within short period of time.