• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.59-65
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• 2000

In this paper the comparison of the first order approximation schemes such as SLP(sequential linear programming) CONLIN(convex linearization) MMA(method of moving asymptotes) and the second order approximation scheme SQP(sequential quadratic programming) was accomplished for optimization of nonlinear structures. It was found that MMA and SQP are the most efficient methods for optimization. But the number of function call of SQP is much more than that of MMA. Therefore when it is considered with the expense of computation MMA is more efficient than SQP. In order to examine the efficiency of MMA for complex optimization problem it was applied to the helicopter tail boom con-sidering column buckling and local wall buckling constraints. it is concluded that MMA can be a very efficient approxima-tion scheme from simple problems to complex problems.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.1
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• pp.90-99
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• 1995

In this study, the algorithm for the optimum design of cantilever retaining wall was de veloped and solved using Modified Method of Feasible Directions(MMFD), Sequential Linear Programming(SLP) and Sequential Quadratic Programming(SQP). The algorithm was applied to the optimum design of 3-different height cantilever re tairing walls. It was shown that even though the starting points and optimization strategies are dif- ferent, the objective function and optimum design variables converge to within a close range, and consequently the reliability and efficiency of the underlying optimum design algorithm can be verified. It is expected that the optimum design algorithm developed in this study can be utilized efficiently for the optimum design of any scale cantilever retaining wall. Using optimum design method, cantilever retaining wall will be designed more economi- cally and reasonably than using traditional design method.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.11
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• pp.447-452
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• 2006

This paper presents a scheme to solve the congestion problem with phase-shifting transformer(PST) controls and power generation controls using linear programming method. A good design of PST and power generation control can improve total transfer capability(TTC) in interconnected systems. This paper deals with an application of optimization technique for TTC calculation. Linear programming method is used to maximize power flow of tie line subject to security constraints such as voltage magnitude and real power flow in interconnected systems. The results are compared with that of repeat power flow(RPF) and sequential quadratic programming(SQP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.111-122
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• 1994

In this study, an algorithm which can be applied to the optimum design of simple steel plate girders was developed, and efficient optimization strategies for the solution of algorithm were found out. The optimum design algorithm consists of 3-levels of optimization. In the first and second levels of optimization, the absolute maximum bending moment and shearing force are extracted and in the third level of optimization, the optimum cross section of steel plate girder is determined. For the optimum design of cross section, the objective function is formulated as the total area of cross section and constraints are derived in consideration of the various stresses and the minimum dimension of flange and web based on the part of steel bridge in the Korea standard code of road bridge. Sequential unconstrained minimization technique using the exterior penalty function method(SUMT-EP), sequential linear programming(SLP) and sequential quadratic programming (SQP) are proved to be efficient and robust strategies for the optimum design of simple plate girder cross section. From the reliable point of view, SLP is the most efficient and robust strategy and SQP is the most efficient one from the viewpoint of converguency and computing time.

• ETRI Journal
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• v.31 no.2
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• pp.121-128
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• 2009

In this paper, we describe a fixed-threshold sequential minimal optimization (FSMO) for structured SVM problems. FSMO is conceptually simple, easy to implement, and faster than the standard support vector machine (SVM) training algorithms for structured SVM problems. Because FSMO uses the fact that the formulation of structured SVM has no bias (that is, the threshold b is fixed at zero), FSMO breaks down the quadratic programming (QP) problems of structured SVM into a series of smallest QP problems, each involving only one variable. By involving only one variable, FSMO is advantageous in that each QP sub-problem does not need subset selection. For the various test sets, FSMO is as accurate as an existing structured SVM implementation (SVM-Struct) but is much faster on large data sets. The training time of FSMO empirically scales between O(n) and O($n^{1.2}$), while SVM-Struct scales between O($n^{1.5}$) and O($n^{1.8}$).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.183-190
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• 2018

This paper presents optimization of the main spar of Human-Powered Aircraft (HPA) wing. Mass minimization was attempted, while considering large torsional deformation of the beam. Sequential Quadratic Programming (SQP) method was adopted as a relevant tool to conduct structural optimization algorithm. An inner diameter and ply thicknesses of the main spar were selected as the design variables. The objective function includes factors such as mass minimization, constant tip bending displacement, and constant tip twist of the beam. For estimation of bending and torsional deformation, the geometrically exact beam model, which is appropriate for large deflection, was adopted. Properties of the cross sectional area which the geometrically exact beam model requires were obtained by Variational Asymptotic Beam Sectional Analysis (VABS), which is a cross sectional analysis program. As a result, maintaining tip bending displacement and tip twist within 1.45%, optimal design that accomplished 7.88% of the mass reduction was acquired. By the stress and strain recovery, structural integrity of the optimal design and validity of the present optimization procedure were authenticated.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.467-474
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• 2018

The purpose of this study is related to automatic hull-form design for ships operating at two speeds. Research was conducted using a series 60 ($C_B=0.6$) ship as a target, which has the most basic ship hull-form. Hull-form development was pursued from the viewpoint of improving resistance performance. In particular, automatic hull-form design for a ship was performed to improve wave resistance, which is closely related to hull-forms. For this purpose, we developed automatic hull-form design software for ships by combining an optimization technique, resistance prediction technique and hull-form modification technique, appling the software developed to a target ship. A sequential quadratic programming method was used for optimization, and a potential-based panel method was used to predict resistance performance. A Gaussian-type modification function was developed and applied to change the ship hull-form. The software developed was used to design a target ship operating at two different speeds, and the performance of the resulting optimized hull was compared with the results of the original hull. In order to verify the validity of the program developed, experimental results obtained in model tests were compared with calculated values by numerical analysis.

• Proceeding of KASS Symposium
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• 2008.05a
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• pp.101-106
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• 2008

This paper describes a comparative study of genetic algorithm and mathematical programming technique applied in the design optimization of geodesic dome. In particular, the genetic algorithm adopted in this study uses the so-called re-birthing technique together with the standard GA operations such as fitness, selection, crossover and mutation to accelerate the searching process. The finite difference method is used to calculate the design sensitivity required in mathematical programming techniques and three different techniques such as sequential linear programming (SLP), sequential quadratic programming(SQP) and modified feasible direction method(MFDM) are consistently used in the design optimization of geodesic dome. The optimum member sizes of geodesic dome against several external loads is evaluated by the codes $ISADO-GA{\alpha}$ and ISADO-OPT. From a numerical example, we found that both optimization techniques such as GA and mathematical programming technique are very effective to calculate the optimum member sizes of three dimensional discrete structures and it can provide a very useful information on the existing structural system and it also has a great potential to produce new structural system for large spatial structures.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1901-1904
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• 2003

MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.

• Proceedings of the KIEE Conference
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• 2001.11b
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• pp.239-242
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• 2001

This paper presents a windows program package for solving security constrained OPF in interconnected power systems, which is based on the combined application of evolutionary programming(EP) and sequential quadratic programming(SQP). The objective functions are the minimization of generation fuel costs and system power losses. The control variables are the active power of the generating units, the voltage magnitude of the generator, transformer tap settings and SVC setting. The state variables are the bus voltage magnitude, the reactive power of the generating unit, line flows and the tie line flow. In OPF considering security, the outages are selected by contingency ranking method. The resulting optimal operating point has to be feasible after outages such as any single line outage(respect of voltage magnitude, reactive power generation and power flow limits). The OPF package proposed is applied to 10 machines 39 buses model system.