• Journal of applied mathematics & informatics
• /
• v.29 no.5_6
• /
• pp.1303-1309
• /
• 2011

Based on the PRP method, a new spectral PRP conjugate gradient method has been proposed to solve general unconstrained optimization problems which produce sufficient descent search direction at every iteration without any line search. Under the Wolfe line search, we prove the global convergence of the new method for general nonconvex functions. The numerical results show that the new method is efficient for the given test problems.

• Journal of applied mathematics & informatics
• /
• v.30 no.5_6
• /
• pp.971-980
• /
• 2012

In this paper, a method associating with one new form of nonmonotone linesearch technique is proposed, which can be regarded as a generalization of the Perry-Shanno memoryless quasi-Newton type method. Under some reasonable conditions, the global convergence of the proposed method is proven. Numerical tests show its efficiency.

• Journal of the Korean Mathematical Society
• /
• v.47 no.1
• /
• pp.63-70
• /
• 2010

In this paper, we develop a nonmonotone spectral memory gradient method for unconstrained optimization, where the spectral stepsize and a class of memory gradient direction are combined efficiently. The global convergence is obtained by using a nonmonotone line search strategy and the numerical tests are also given to show the efficiency of the proposed algorithm.

• Journal of applied mathematics & informatics
• /
• v.24 no.1_2
• /
• pp.367-376
• /
• 2007

In this paper we consider the global convergence of a new super memory gradient method for unconstrained optimization problems. New trust region radius is proposed to make the new method converge stably and averagely, and it will be suitable to solve large scale minimization problems. Some global convergence results are obtained under some mild conditions. Numerical results show that this new method is effective and stable in practical computation.

• Journal of applied mathematics & informatics
• /
• v.22 no.1_2
• /
• pp.461-466
• /
• 2006

In this paper, an algorithm with a new Armijo-type line search is proposed that ensure global convergence of a correlative Polak-Ribiere conjugate method for the unconstrained minimization of non-convex differentiable function.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.7 s.100
• /
• pp.829-835
• /
• 2005

An optimization formulation of unconstrained damping treatment on beam is proposed to minimize vibration responses using a numerical search method. The fractional derivative model is combined with RUK's equivalent stiffness approach in order to represent nonlinearity of complex modulus of damping materials with frequency and temperature. Vibration responses are calculated by using the modal superposition principle, and of which design sensitivity formula with respect to damping layout is derived analytically. Plugging the sensitivity formula into optimization software, we can determine optimally damping treatment region that gives minimum forced response under a given boundary condition. A numerical example shows that the proposed method is very effective in suppressing nitration responses by means of unconstrained damping layer treatment.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.519-524
• /
• 1996

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are applicaiton of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained optimization problem into an unconstrained one and premature convergence of solution. Thus, we developed an modified GAs to solve this problems, and two examples are given to demonstrate the effectiveness of the methodology developed in this paper.

• Communications of the Korean Mathematical Society
• /
• v.33 no.2
• /
• pp.671-676
• /
• 2018

In this paper we prove that the gradient ideal of a Morse polynomial is radical. This gives a generic class of polynomials whose gradient ideals are radical. As a consequence we reclaim a previous result that the unconstrained polynomial optimization problem for Morse polynomials has a finite convergence.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.18 no.11
• /
• pp.2825-2836
• /
• 1994

The engineering optimization has been developed for the automatic design of engineering systems. Since the conventional optimum is determined without considering noise factors, applications to practical problems can be limited. Current design practice tends to account for these noises by the specification of closer tolerances or the use of safety factors. However, these approaches may be very expensive. Thus the consideration on the noises of design variables is needed for optimal design. A method is presented to find robust solutions for unconstrained optimization problems. The method is applied to discrete and continuous variables. The orthogonal array is utilized based on the Taguchi concept. Through mathematical proofs and numerical examples, it is verified that solutions from the suggested method are more insensitive than the conventional optimum within the range of variations for design variables.

• The Journal of Korea Robotics Society
• /
• v.2 no.4
• /
• pp.327-333
• /
• 2007

We propose a navigation algorithm using image-based visual servoing utilizing a fixed camera. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the image error between the goal position and the position of a mobile robot. The residual function which is the image error between the position of a mobile robot and the goal position is generally large for this navigation problem. So, this navigation problem can be considered as the nonlinear least squares problem for the large residual case. For large residual, we propose a method to find the second-order term using the secant approximation method. The performance was evaluated using the simulation.