• Bulletin of the Korean Mathematical Society
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• v.60 no.4
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• pp.1101-1129
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• 2023

In this study we propose a model of optimal retirement, consumption and portfolio choice of an individual agent, which encompasses a large class of the models in the literature, and provide a methodology to solve the model. Different from the traditional approach, we consider the problems before and after retirement simultaneously and identify the difference in the dual value functions as the utility value of lifetime labor. The utility value has an option nature, namely, it is the maximized value of choosing the retirement time optimally and we discover it by solving a variational inequality. Then, we discover the dual value functions by using the utility value. We discover the value function and optimal policies by establishing a duality between the value function and the dual value function. The model and approach offer a significant advantage for computation of optimal policies for a large class of problems.

• Journal of Biomedical Engineering Research
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• v.39 no.3
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• pp.134-139
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• 2018

One of the most common problems with pedicle screw system is pullout of the screw. This study was performed to evaluate the pullout strength and driving torque of newly designed pedicle screws. The design of three type screws were standard pedicle screw, which had single lead threaded and single pitched design (Type A), single pitched and dual lead threaded pedicle screw (Type B), dual pitched and dual lead threaded pedicle screw (Type C), respectively. The tests were performed in accordance with the ASTM standards using polyurethane (PU) foam blocks. There was no significant difference in pullout strength among three types of screw. Type B and Type C exhibited higher insertion torque and removal torque than Type A, respectively (p<0.05). Pedicle screws newly developed with dual pitched and dual lead threaded design showed higher driving torque without decrease in pullout strength compared to the standard pedicle screw and could be inserted more rapidly with the same number of revolutions.

• Journal of applied mathematics & informatics
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• v.32 no.1_2
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• pp.153-159
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• 2014

In this paper, we introduce a pair of higher-order symmetric dual models/problems. Weak, strong and converse duality theorems for this pair are established under the assumption of higher-order invexity. Moreover, self duality theorem is also discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.308-311
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• 2008

The ant colony optimization (ACO) is a metaheuristic inspired by the behavior of real ants. Recently, ACO has been widely used to solve the difficult combinatorial optimization problems. In this paper, we propose an ACO algorithm to solve the two disjoint paths problem with dual link cost structure (TDPDCP). We propose a dual pheromone structure and a procedure for solution construction which is appropriate for the TDPDCP. Computational comparisons with the state-of-the-arts algorithms are also provided.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.475-488
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• 1998

Wolfe and Mond-Weir type duals for multiobjective con-trol problems are formulated. Under pseudo-invexity/quasi-invexity assumptions of the functions involved, weak and strong duality the-orems are proved to relate efficient solutions of the primal and dual problems.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.6
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• pp.396-405
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• 2019

Single-phase full-bridge inverters have shoot-through problems. Dead time is an essential way of solving these issues, but it distorts the output voltage and current. Dual-buck inverters are designed to eliminate the abovementioned problems. However, these inverters result in switching power loss and electromagnetic interference due to the diode reverse-recovery problem. Previous studies have suggested reducing the switching power loss from diode reverse-recovery, but their proposed methods have complex circuit configurations and high system costs. To alleviate the switching power loss from diode reverse-recovery, the current work proposes a dual-buck inverter with a coupled inductor. In the structure of the proposed inverter, the current flowing into the original diode is divided into a new diode. Therefore, the switching power loss is reduced, and the efficiency of the proposed inverter is improved. Simulation waveforms and experimental results for a 1.0 kW prototype inverter are discussed to verify the performance of the proposed inverter.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11a
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• pp.46-51
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• 2001

To reach high areal density, less track pitch is expected and more servo bandwidth is required. One approach to overcoming the problem is by using dual stage servo system. In this system, a voice coil motor (VCM) is used as the primary stage while a milliactuator is used as the secondary stage. We have suggested new milliactuator based on the shear mode of piezoelectric elements to drive the head suspension assembly. In this paper, we introduce controller design method, PQ method. PQ method reduces the controller design problem for DISO(dual-input/single-output) systems to two standard controller design problems for SISO(single-input/single-output) problems. The first part of PQ method directly address the issue of actuator output contribution, and the second part allows the use of traditional loop shaping to achieve the overall system performance. This paper shows how to employ the PQ method to meet aggressive close-loop performance specifications for a disk drive system with a VCM and piezoelectric milliactuator.

• The Journal of Information Technology
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• v.3 no.2
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• pp.73-85
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• 2000

The efficient algorithms are suggested in this study for solving the multicommodity network flow problems applied to Communications Systems. These problems are typical NP-complete optimization problems that require integer solution and in which the computational complexity increases numerically in appropriate with the problem size. Although the suggested algorithms are not absolutely optimal, they are developed for computationally efficient and produce near-optimal and primal integral solutions. We supplement the traditional Lagrangian method with a price-directive decomposition. It proceeded as follows. First, A primal heuristic from which good initial feasible solutions can be obtained is developed. Second, the dual is initialized using marginal values from the primal heuristic. Generally, the Lagrangian optimization is conducted from a naive dual solution which is set as ${\lambda}=0$. The dual optimization converged very slowly because these values have sort of gaps from the optimum. Better dual solutions improve the primal solution, and better primal bounds improve the step size used by the dual optimization. Third, a limitation that the Lagrangian decomposition approach has Is dealt with. Because this method is dual based, the solution need not converge to the optimal solution in the multicommodity network problem. So as to adjust relaxed solution to a feasible one, we made efficient re-allocation heuristic. In addition, the computational performances of various versions of the developed algorithms are compared and evaluated. First, commercial LP software, LINGO 4.0 extended version for LINDO system is utilized for the purpose of implementation that is robust and efficient. Tested problem sets are generated randomly Numerical results on randomly generated examples demonstrate that our algorithm is near-optimal (< 2% from the optimum) and has a quite computational efficiency.

• Journal of the Korean Operations Research and Management Science Society
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• v.24 no.1
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• pp.27-38
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• 1999

In this paper, Primal-Interior Dual-Simplex method(PIDS) and Dual-Interior Primal-Simplex method(DIPS) are developed for the general bounded linear programming. Two methods were implemented and compared with other pricing techniques for the Netlib. linear programming problems. For the PIDS, it shows superior performance to both most nagative rule and dual steepest-edge method since it practically reduces degenerate iterations and has property to reduce the problem. For the DIPS, pt requires less iterations and computational time than least reduced cost method. but it shows inferior performance to the dynamic primal steepest-edge method.

• Journal of the Korean Mathematical Society
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• v.47 no.1
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• pp.17-28
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• 2010

In this paper we deal with linear chance-constrained optimization problems, a class of problems which naturally arise in practical applications in finance, engineering, transportation and scheduling, where decisions are made in presence of uncertainty. After giving the deterministic equivalent formulation of a linear chance-constrained optimization problem we construct a conjugate dual problem to it. Then we provide for this primal-dual pair weak sufficient conditions which ensure strong duality. In this way we generalize some results recently given in the literature. We also apply the general duality scheme to a portfolio optimization problem, a fact that allows us to derive necessary and sufficient optimality conditions for it.