• Journal of Industrial Technology
• /
• v.22 no.A
• /
• pp.19-28
• /
• 2002

The Nelder-Mead simplex algorithm has been one of the most widely used methods for the nonlinear unconstrained optimization, since 1965. Recently, the new algorithm, (so-called the Fuzzy Simplex Algorithm), with fuzzy logic controllers for the expansion, reflection and contraction process of this algorithm has been proposed. In this paper, this new algorithm is developed. And, the formulation for the optimum design of the power screw's efficiency is made. And then, the developed fuzzy simplex algorithm as well as the original one is applied to this optimum design problem. The Fuzzy simplex algorithm results in a faster convergence in this problem, as reported in other study, too.

• Journal of Industrial Technology
• /
• v.20 no.B
• /
• pp.27-34
• /
• 2000

The definition of flatness is given by ISO, ANSI, KS, etc. but those standards don't mention about the specific methods for the flatness. So various solution models that are based on the Minimum Zone Method have been proposed as an optimization problem for the minimax curve fitting. But it has been rare to compare some optimization algorithms to make a guideline for choosing better algorithms in this field. Hence this paper examined and compared Genetic Algorithm and Simplex Method to the evaluation of flatness. As a result, Genetic Algorithm gave the better or equal flatness than Simplex Method but it has the inefficiency caused from the large number of iteration. Therefore, in the future, another researches about alternative algorithms including Hybrid Genetic Algorithm should be achieved to improve the efficiency of Genetic Algorithm for the evaluation of flatness.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 2002.10b
• /
• pp.399-400
• /
• 2002

A numerical procedure for analyzing thermo-elastic contact applied to an automotive disk brake and calculating subsurface stress distribution has been developed. The proposed procedure takes the advantage of the simplex algorithm to save computing time. Flamant's solution and Boussinesq's solution are adopted as Green function in analysis. Comparing the numerical results with the exact solutions has proved the validity of this procedure.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.3A
• /
• pp.249-253
• /
• 2006

We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.

• Proceedings of the KSME Conference
• /
• 2001.11a
• /
• pp.533-538
• /
• 2001

This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a genetic algorithm and a local concentrate search algorithm (e. g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.26 no.6
• /
• pp.1008-1015
• /
• 2002

This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2000.11a
• /
• pp.587-592
• /
• 2000

The optimization method based on an enhanced genetic algorithms is proposed for multimodal function optimization in this paper. This method is consisted of two main steps. The first step is global search step using the genetic algorithm(GA) and function assurance criterion(FAC). The belonging of an population to initial solution group is decided according to the FAC. The second step is to decide the similarity between individuals, and to research the optimum solutions by simplex method in reconstructive search space. Two numerical examples are also presented in this paper to comparing with conventional methods.

• Journal of Industrial Technology
• /
• v.22 no.B
• /
• pp.35-44
• /
• 2002

To find the optimal solution as rapidly and exactly as possible with Nelder-Mead simplex algorithm, the present values of the reflection, expansion, contraction and/or shrink parameters of this algorithm are needed to be changed at appropriate time during the search process. The reflection parameter is selected in this study in order to be changed because reflection, expansion and contraction process can be simultaneously effected by only this parameter. Two independent indices for determining whether the present value of the reflection parameter of this algorithm should be changed or not during the search process are suggested in this study. Those indices were made of the equations of Nelder-Mead simplex algorithm's convergence criterion and Dennis-Wood's convergence criterion, respectively. It is appeared that the optimal solution can be find with smaller numbers of objective function evaluation than the original Nelder-Mead's one with fixed parameter when the those indices are used during the search process. and the more remarkable reduction effect of the number of an objective function evaluation can be obtained when the latter index is used.

• KIISE Transactions on Computing Practices
• /
• v.21 no.1
• /
• pp.94-99
• /
• 2015

With the recent machine learning paradigm of using nonparametric Bayesian statistics and statistical inference based on random sampling, the Dirichlet distribution finds many uses in a variety of graphical models. It is a multivariate generalization of the gamma distribution and is defined on a continuous (K-1)-simplex. This paper presents a sampling method for a Dirichlet distribution for the problem of dividing an integer X into a sequence of K integers which sum to X. The target samples in our problem are all positive integer vectors when multiplied by a given X. They must be sampled from the correspondingly gridded simplex. In this paper we develop a Markov Chain Monte Carlo (MCMC) proposal distribution for the neighborhood grid points on the simplex and then present the complete algorithm based on the Metropolis-Hastings algorithm. The proposed algorithm can be used for the Markov model, HMM, and Semi-Markov model for accurate state-duration modeling. It can also be used for the Gamma-Dirichlet HMM to model q the global-local duration distributions.

• Korean Management Science Review
• /
• v.11 no.3
• /
• pp.13-26
• /
• 1994

In this paper we studied an integration scheme of some simplex algorithms and some efficient techniques to get the stable solution in linear programming code. And we developed a linear programming package (LPAK) by introducing this scheme and techniques. In LPAK three different algorithms were integrated, which were two primal simplex algorithms using Two phase method and big-M method respectively, and the dual simplex algorithm. LPAK introduces several heuristic techniques in each step of simplex method in order to enhance the stability and efficiency. They were new heuristic methods in structuring initial basis, choosing entering variable, choosing dropping variable and performing reinversion. The experimental results on the NETLIB problems showed that LPAK provided the stable solutions.