• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.5
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• pp.217-224
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• 2002

This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.14 no.2
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• pp.93-111
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• 2010

The purpose of this paper is to obtain new complexity results for a second-order cone optimization (SOCO) problem. We define a proximity function for the SOCO by a kernel function. Furthermore we formulate an algorithm for a large-update primal-dual interior-point method (IPM) for the SOCO by using the proximity function and give its complexity analysis, and then we show that the new worst-case iteration bound for the IPM is $O(q\sqrt{N}(logN)^{\frac{q+1}{q}}log{\frac{N}{\epsilon})$, where $q{\geqq}1$.

• International Journal of Automotive Technology
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• v.6 no.6
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• pp.635-641
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• 2005

This paper presents an ASF (Aluminum Space Frame) BIW (Body in White) optimal design, which minimizes weight and satisfies multidisciplinary constraints such as static stiffness, vibration characteristics, low-/high-speed crash, and occupant safety. As only one cycle CPU time for all the analyses is 12 hours, the ASF design having 11-design variable is a large scaled problem. In this study, ISCD-II and conservative least square fitting method were used for efficient RSM modeling. Likewise, the ALM method was used to solve the approximate optimization problem. The approximate optimum was sequentially added to remodel the RSM. The proposed optimization method uses only 20 analyses to solve the 11-design variable problem. Moreover, the optimal design can achieve $15.6\%$ weight reduction while satisfying all the multidisciplinary design constraints.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.786-792
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• 2011

The present paper presents an optimal capacitor placement (OCP) algorithm for voltagestability enhancement. The OCP issue is represented using a mixed-integer problem and a highly nonlinear problem. The hybrid particle swarm optimization (HPSO) algorithm is proposed to solve the OCP problem. The HPSO algorithm combines the optimal power flow (OPF) with the primal-dual interior-point method (PDIPM) and ordinary PSO. It takes advantage of the global search ability of PSO and the very fast simulation running time of the OPF algorithm with PDIPM. In addition, OPF gives intelligence to PSO through the information provided by the dual variable of the OPF. Numerical results illustrate that the HPSO algorithm can improve the accuracy and reduce the simulation running time. Test results evaluated with the three-bus, New England 39-bus, and Korea Electric Power Corporation systems show the applicability of the proposed algorithm.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.96-104
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• 2006

We propose a path planning method to improve the productivity of AOI (automated optical inspection) machines in PCB (printed circuit board) assembly lines. The path-planning problem is the optimization problem of finding inspection clusters and the visiting sequence of cameras to minimize the overall working time. A unified method is newly proposed to determine the inspection clusters and visiting sequence simultaneously. We apply a hybrid genetic algorithm to solve the highly complicated optimization problem. Comparative simulation results are presented to verify the usefulness of the proposed method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1992.04a
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• pp.73-78
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• 1992

A stochastic simulated anneal ins (SSA) is a recent approach to the solution of problems characterized by large number of interacting degrees of freedom. SSA simulates the degrees of freedom in a problem in a such a way that they are a collection of atoms slowly being coolded into a ground state which would correspond to the stationary point of the problem. In this paper, for a randomly disturbed current design, SSA optimization technique is used, which establishes a probabilistic criterion for acceptance or rejection of current design and iteratively improves it to arrive at a stationary Point at which critical temperature is reached. Simple truss optimization problem which consider as their constraints only the tensile and compressive yielding strength of the members are tested using SSA. Satisfactory results are obtained and some discussions are given for the behavior of SSA on the tested truss structures.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.25-31
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• 2018

In this paper, we consider the game theoretic approach to investigate the transmit power optimization problem where D2D users share the uplink of the cellular system. Especially, we formulate the transmit power optimization problem as a non cooperative power control game. In the user wide sense, each user may try to select its transmit power level so as to maximize its utility in a selfish way. In the system wide, the transmit power levels of all users eventually converge to the unique point, called Nash Equilibrium. We first formulate the transmit power optimization problem as a non cooperative power control game. Next, we examine the existence of Nash Equilibrium. Finally, we present the numerical example that shows the convergence to the unique transmit power level.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.71-73
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• 1995

This paper presents an optimization technique using genetic algorithms(GA) for loss minimization in the distribution network reconfiguration. Determining switch position to be opened for loss minimization in the radial distribution system is a discrete optimization problem. GA is appropriate to solve the multivariable optimization problem and it uses population, not a solution. For this reason, GA is attractive to solve this problem. In this paper, we aimed at finding appropriate open sectionalizing switch position using GA, which can lead to minimum transmission losses.

• Smart Structures and Systems
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• v.19 no.4
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• pp.449-461
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• 2017

One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.4
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• pp.197-209
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• 2012

This paper studies an emergency service vehicle location problem, where minimum reliability level pre-specified at each demand point is assured. Several models are suggested depending on the busy fraction, which is the time proportion of unavailability for the ambulances. In this paper a new model on computing the busy fraction is suggested, where it varies depending on the distance between the demand point and ambulances, hence it may respond the more realistic situation. The busy fraction for the ambulance location determined by the optimization model is computed by the simulation, and updated through the iterative procedure. It has been shown that the performances of the solutions obtained by the algorithm suggested for the instances appeared in the literature.