• Journal of Mechanical Science and Technology
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• v.14 no.3
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• pp.306-313
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• 2000

The homogenization method and the density function method are common approaches to evaluate the equivalent material properties for design cells composed of matter and void. In this research, using a new topology optimization method based on the homogenized material with a penalty factor and the chessboard prevention strategy, we obtain the optimal layout of a structure for the natural frequency of a designated mode. The volume fraction of nodes of each finite element is chosen as the design variable and a total material usage constraint is imposed. In this paper, the subspace method is used to evaluate the eigenvalue and its corresponding eigenvector of the structure for the designated mode and the recursive quadratic programming algorithm, PLBA algorithm, is used to solve the topology optimization problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.64-74
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• 2014

We show how a supplier can peg cost measures to the reliability of his time guarantees via the penalty costs considered in the framework. The framework also enables us to study the connections between the logistics network and the market. In this context, we show that even when the market base increases significantly, the supplier can still use the logistics network designed to satisfy lower demand density, with only a marginal reduction in profit. Finally we show how the framework is useful to evaluate and compare various logistics system improvement strategies. The supplier can then easily choose the improvement strategy that increases his profit with the minimal increase in his logistics costs.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.928-933
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• 2001

EGR(Exhaust Gas Recirculation) is an effective strategy to control nitrogen oxides emissions from diesel engine. The EGR reduces $NO_x$ through lowering the oxygen concentration in the combustion chamber as well as through heat absorption. However, application of EGR system is difficult because of the penalty in fuel consumption and the increase in particulate matter. The engine used for the experimental was a 3-cylinder 0.8-liter turbo-charged light duty diesel engine with an electronic EGR valve. In this study, experiments were performed at variable vehicle speeds and loads on the chassis dynamometer. To evaluate the exhaust emissions with the EGR system testing was performed using cvs-75 mode test procedure. Results of the cvs-75 mode test achieve sufficiently to meet EURO3 standards.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.732-735
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• 1999

A GA-based optimization technique is adopted in the paper to obtain optimal future control inputs for predictive control systems. For reliable future predictions of a process, we identify the underlying process with an NNARX model structure and investigate to reduce the volume of neural network based on the Lipschitz index and a criterion. Since most industrial processes are subject to their constraints, we deal with the input-output constraints by modifying some genetic operators and/or using a penalty strategy in the GAPC. Some computer simulations are given to show the effectiveness of the GAPC method compared with the adaptive GPC algorithm.

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.981-1000
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• 2009

This paper considers asset liability management problems when their deterministic equivalent formulations are general nonlinear optimization problems. The presented approach uses a nonmonotone trust region strategy for solving a sequence of unconstrained subproblems parameterized by a scalar parameter. The objective function of each unconstrained subproblem is an augmented penalty-barrier function that involves both primal and dual variables. Each subproblem is solved approximately. The algorithm does not restrict a monotonic decrease of the objective function value at each iteration. If a trial step is not accepted, the algorithm performs a non monotone line search to find a new acceptable point instead of resolving the subproblem. We prove that the algorithm globally converges to a point satisfying the second-order necessary optimality conditions.

• Journal of Contemporary Eastern Asia
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• v.14 no.2
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• pp.17-36
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• 2015

As an effort of mitigating hazards, pro-environmental programs have been vigorously activated with regard to solid waste recycling. It is beneficial for both the environment and resource saving, but implementation and enforcement are hard to achieve voluntarily. The South Korean Government first implemented the Deposit Refund System (DRS) and later the Extended Producer Responsibility Program (EPR) to reduce waste and encourage recycling in South Korea. Un-der the DRS, producers would pay for recycling the wastes of the products. The government then repealed the DRS and implemented the EPR program. Under this program, the producers recycle as much as the Ministry of Environment determines or pay a penalty for an excessive amount of the waste. In the broader perspective of disaster management, such policy programs can mitigate environmental hazards. This paper compares those two programs that facilitated the level of recycling, focusing on how such programs regulate producers and how they were operated from the perspective of implementation and enforcement.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.42.3-42
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• 2001

A human is an expert in manipulation. We have acquired skills to perform dexterous operations based upon knowledge and experience attained over a long period of time. It is important in robotics to understand these human skills, and utilize them to bring about better robot control and operation It is hoped that the neurocontroller can be trained and organized by simply presenting human teaching data, which implicate human intention, strategy and expertise. In designing a neurocontroller, we must determine the size of neurocontroller. Improper size may not only incur difficulties in training neural nets, e.g. no convergence, but also cause instability and erratic behavior in machines. Therefore, it is necessary to determine the proper size of neurocontroller for human control transfer. In this paper, a new pruning method is developed, based on the penalty-term methods. This method makes ...

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.563-575
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• 2023

Trajectory planning is a key technology for unmanned aerial vehicles (UAVs) to achieve complex flight missions. In this paper, a terminal constraints conversion-based Gauss pseudospectral trajectory planning optimization method is proposed. Firstly, the UAV trajectory planning mathematical model is established with considering the boundary conditions and dynamic constraints of UAV. Then, a terminal constraint handling strategy is presented to tackle terminal constraints by introducing new penalty parameters so as to improve the performance index. Combined with Gauss-Legendre collocation discretization, the improved Gauss pseudospectral method is given in detail. Finally, simulation tests are carried out on a four-quadrotor UAV model with different terminal constraints to verify the performance of the proposed method. Test studies indicate that the proposed method performances well in handling complex terminal constraints and the improvements are efficient to obtain better performance indexes when compared with the traditional Gauss pseudospectral method.

• Nuclear Engineering and Technology
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• v.27 no.5
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• pp.721-729
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• 1995

The Korean optimal nuclear fuel cycle strategy from the year 2000 to 2030 is derived using linear programming. The fuel cycle cost, the cost uncertainty, and the natural uranium consumption are used as the criteria for the optimization. These objectives are compromised by fuzzy decision-making technique which maximizes the minimum degree of satisfaction among the three objectives. The options for the back-end fuel cycle are direct disposal, reprocessing, and DUPIC. The optimal fuel cycle strategy of Korea is to start reprocessing in around 2010 and increase its capacity with the maximum of 800 tHM in around 2025, and to star DUPIC processing in 2025. The cot uncertainty and the natural uranium consumption of the optimal fuel cycle strategy are reduced by 7.1％ and 6.1％, respectively, at the cost penalty of 5.4％ compared with the cost-only optimal solution.

• Journal of Advanced Navigation Technology
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• v.13 no.1
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• pp.87-96
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• 2009

The purpose of this paper is to analyze the power control problem in wireless communications with game theoretic approach. The major contribution of the present paper is that we formulated the problem as a game with a finite number of strategies while most of the previous game theoretic power control literatures modeled with continuous game in which there are infinite number of strategies. It should be noted that the closed-loop power control would be performed in a discrete manner, power up or down from the present level of power with fixed power control step size. We model the current closed-loop power control scheme with the famous Prisoner's dilemma model and show that the power-up strategy is Nash equilibrium. That is, every mobile tries to increase their power and approach to their maximal power. Thus, the outcome of current power control (Nash equilibrium) is inefficient. In order to attain efficient power control for the environment where ICI(Inter-Cell Interference is severe, we developed a new payoff function in which the penalty mechanism is introduced and derived conditions under which power-down becomes Nash equilibrium strategy for all players. Furthermore we examined the trajectory of equilibrium power when the power control game will be played repeatedly.