• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.213-216
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• 2005

In this research, we explore how to manage the transition of technology generations considering incremental innovation of the existing technology generation. Firms can slow down decaying of the existing technology by continuous incremental improvements rather than introducing a new generation technology at the first time if the former strategy is better. We characterize optimal technology transition problem by setting up an optimal control model. The model which is originally designed and solved by Thompson(1968) as a ‘Machine maintenance problem’ has been cited to build the main body of our model. With this analytical model, we derive optimal ‘incremental innovation’ strategy which is considering transition to the next technology. Our analysis indicates that there exists an unique ‘stopping incremental innovation timing’. Before the point of time, the decision maker should make his effort at a maximum level to enhance the current technology. However from the stopping timing to the final time horizon where the new technology is introduced, it is found that not to invest to the current technology any more is optimal.

• Bulletin of the Korean Mathematical Society
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• v.48 no.5
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• pp.1079-1092
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• 2011

We consider the Newton's method for an direct solver of the optimal control problems of the Navier-Stokes equations. We show that the finite element solutions of the optimal control problem for Stoke equations may be chosen as the initial guess for the quadratic convergence of Newton's algorithm applied to the optimal control problem for the Navier-Stokes equations provided there are sufficiently small mesh size h and the moderate Reynold's number.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.533-539
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• 1993

In this paper, two side-attack guidance laws for an underwater vehicle are considered. In order to find the guidance command, we first make use of the optimal guidance law with terminal impact angle constraint. Secondly, the optimal solution of tracking problem is used. This paper shows some brief theory which is used in deriving the side-attack guidance laws, and the method of computing these guidance laws. Simulations on underwater vehicle for a constant moving target prove that the suggested side-attack guidance laws have enhanced side attack performance over the optimal guidance law with miss distance weighting only. Furthermore, from simulation results. we conclude that the guidance law using the optimal solution of tracking problem is more efficient for the side-attack guidance than the optimal guidance law with terminal impact angle constraint.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2076-2080
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• 2005

Study in this paper concerns the optimal $H_{2}$ integral servo problems for linear crane model systems via the constraints of the derivatives of state variables added to the standard constraints. It is shown in the paper that the derivative state constrained optimal $H_{2}$ integral servo problems can be reduced to the standard optimal $H_{2}$ control problem. The main subject of the paper is to apply the results of derivative state constrained $H_{2}$ integral servo theorem in crane system. The effect of our proposed controller with respect to mitigate an under damping for crane model system is also verified.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.432-435
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• 1995

In this paper a new approach to obtain the solution of the linear-quadratic Gaussian control problem for singularly perturbed discrete-time stochastic systems is proposed. The alogorithm proposed is based on exploring the previous results that the exact solution of the global discrete algebraic Riccati equations is found in terms of the reduced-order pure-slow and pure-fast nonsymmetric continuous-time algebraic Riccati equations and, in addition, the optimal global Kalman filter is decomposed into pure-slow and pure-fast local optimal filters both driven by the system measurements and the system optimal control input. It is shown that the optimal linear-quadratic Gaussian control problem for singularly perturbed linear discrete systems takes the complete decomposition and parallelism between pure-slow and pure-fast filters and controllers.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.926-931
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• 2008

In order to design a high-performance controller with excellent positioning and tracking performance, an optimal tuning method based on the integrated design concept is studied. DOBs, feedforward controllers and CCC are applied to control the bi-axial linear servomechanism. To derive accurate dynamic models of mechanical subsystems equipped with linear servos for the integrated tuning, system identification processes are conducted through the sine sweeping. An optimal tuning problem with stability, robustness and overshoot constraints is formulated as a nonlinear constrained optimization problem. Optimal gains are obtained through the SQP method. Experimental results confirm that both tracking and contouring errors are significantly reduced by applying the proposed controller and integrated tuning method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.6
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• pp.302-310
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• 2002

This paper presents an application of a improved branch exchange (IBE) algorithm with a tie branch power (TBP) flow equation to solve the Optimal Routing problem for operation of a radial Power system including power distribution system. The main objective of the Optimal Routing problem usually is to minimize the network real power loss and to improve the voltage profile in the network. The new BE algorithm adopts newly designed methods which are composed by decision method of maximum loss reduction and new index of loss exchange in loop network Thus, the proposed algorithm in this paper can search the optimal topological structures of distribution feeders by changing the open/closed states of the sectionalizing and tie switches. The proposed algorithm has been evaluated with the practical IEEE 32, 69 bus test systems and KEPCO 148 bus test system to show favorable performance gained.

• Management Science and Financial Engineering
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• v.19 no.2
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• pp.43-47
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• 2013

This paper studies an optimal consumption and portfolio choice problem for unemployed people who have an option to work. Our problem is to find optimal consumption, risky investment, and workforce re-entry strategies for the unemployed. We find a closed form of the critical wealth level to re-enter the workforce. We show that the unemployed with a higher disutility of labor or a larger relative risk aversion are more reluctant to re-enter the workforce.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.

• Journal of the Korea Society of Computer and Information
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• v.20 no.12
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• pp.75-82
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• 2015

Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.