• Journal of the Korean Society for Railway
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• v.2 no.3
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• pp.9-17
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• 1999

This paper presents a new algorithm to determine the pre-loads that sustain the static equilibrium state in a given position. The algorithm which uses a partial velocity matrix leads to an unconstrained optimization problem to compute the pre-loads of the suspensions. To demonstrate the validity of the proposed algorithm, the static analysis results that employ the pre-loads of three examples are presented using a reliable commercial program. Results of the analysis confirm the validity of the proposed algorithm.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.1
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• pp.117-127
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• 2008

The performance of a modified Armijo line search rule related to BFGS gradient type method with the results from other well-known line search rules are compared as well as analyzed. Although the modified Armijo rule does require as much computational cost as the other rules, it shows more efficient in finding local minima of unconstrained optimization problems. The sensitivity of the parameters used in the line search rules is also analyzed. The results obtained by implementing algorithms in Matlab for the test problems in [3] are presented.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.744-746
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• 2000

This paper presents an optimum design of a linear induction motor(LIM) using genetic algorithm(GA). Sequential unconstrained minimization technique(SUMT) is used to transform the nonlinear optimization with constraints to a simple unconstrained problem. The objective functions of LIM such as trust, weight are optimized and the result was applied to the design of linear induction pump.

• Earthquakes and Structures
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• v.10 no.6
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• pp.1451-1465
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• 2016

The effectiveness of base isolation (BI) systems for mitigation of seismic vibration of bridges have been extensively studied in the past. It is well established in those studies that the performance of BI system is largely dependent on the characteristics of isolator yield strength. For optimum design of such systems, normally a standard nonlinear optimization problem is formulated to minimize the maximum response of the structure, referred as Stochastic Structural Optimization (SSO). The SSO of BI system is usually performed with reference to a problem of unconstrained optimization without imposing any restriction on the maximum isolator displacement. In this regard it is important to note that the isolator displacement should not be arbitrarily large to fulfil the serviceability requirements and to avoid the possibility of pounding to the adjacent units. The present study is intended to incorporate the effect of excessive isolator displacement in optimizing BI system to control seismic vibration effect of bridges. In doing so, the necessary stochastic response of the isolated bridge needs to be optimized is obtained in the framework of statistical linearization of the related nonlinear random vibration problem. A simply supported bridge is taken up to elucidate the effect of constraint condition on optimum design and overall performance of the isolated bridge compared to that of obtained by the conventional unconstrained optimization approach.

• Proceedings of the KIEE Conference
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• 1993.07b
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• pp.923-928
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• 1993

Genetic algorithms are powerful optimization methods based on the mechanism of natural genetics and natural selection. Genetic algorithms reduce chance of searching local optima unlike most conventional search algorithms and especially show good performances in complex nonlinear optimization problems because they do not require any information except objective function value. This paper presents a new model based on sexual reproduction in nature. In the proposed Sexual Reproduction model(SR model), individuals consist of the diploid of chromosomes, which are artificially coded as binary string in computer program. The meiosis is modeled to produce the sexual cell(gamete). In the artificial meiosis, crossover between homologous chromosomes plays an essential role for exchanging genetic informations. We apply proposed SR model to optimization of the design parameters of Single-sided Linear Induction Motor(SLIM). Sequential Unconstrained Minimization Technique(SUMT) is used to transform the nonlinear optimization problem with many constraints of SLIM to a simple unconstrained problem, We perform optimal design of SLIM available to FA conveyer systems and discuss its results.

• Journal of applied mathematics & informatics
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• v.5 no.3
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• pp.701-716
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• 1998

In this paper we develop algorithms in programming lan-guage SCHEME for implementation of the main first order gradient techniques for unconstrained optimization. Implementation of the de-scent techniques which use non-optimal descent steps as well as imple-mentation of the optimal descent techniques are described. Also we investigate implementation of the global problem called optimization along a line. Developed programs are effective and simpler with re-spect to the corresponding in the procedural programming languages. Several numerical examples are reported.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.481-488
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• 1998

The drift and inter-story drift control method for steel structures subjected to seismic forces is formulated into a structural optimization problem in this paper. The formulated optimization problem with constraints on drift, inter-story drifts, and member strengthes are transformed into an unconstrained optimization problem. For the solution of the tranformed optimization problem an searching algorithm based on the gradient projection method utilizing gradient information on eigenvalues and eigenvectors are developed and presented in detail. The performance of the proposed algorithm is demonstrated by application to drift control of a verifying example.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.239-254
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• 2006

An efficient descent method for unconstrained optimization problems is line search method in which the step size is required to choose at each iteration after a descent direction is determined. There are many ways to choose the step sizes, such as the exact line search, Armijo line search, Goldstein line search, and Wolfe line search, etc. In this paper we propose a new inexact line search for a general descent method and establish some global convergence properties. This new line search has many advantages comparing with other similar inexact line searches. Moreover, we analyze the global convergence and local convergence rate of some special descent methods with the new line search. Preliminary numerical results show that the new line search is available and efficient in practical computation.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.805-812
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• 2006

An optimization formulation is proposed to minimize sound pressures in a two-dimensional cavity by controlling the attachment area of unconstrained damping materials. For the analysis of structural-acoustic systems, a hybrid approach that uses finite elements for structures and boundary elements for cavity is adopted. Four-parameter fractional derivative model is used to accurately represent dynamic characteristics oJ the viscoelastic materials with frequency and temperature. Optimal layouts of the unconstrained damping layer on structural wall of cavity are identified according to temperatures and the amount of damping material by using a numerical search 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.