• Transactions of the Society of Information Storage Systems
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• v.3 no.4
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• pp.178-182
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• 2007

Topology optimization methods are classified into two methods such as the density method and the homogenization method. Those methods need to consider relationships between the material property and the density of each element in a design domain, the relaxation of the design space, etc. However, it is hard to apply on some cases due to the complexity to compose the design objective and its sensitivity analysis. In this paper, a modified topology optimization is proposed to assist designers who do not have mathematical or theoretical background of the topology optimization. In this study, optimal topology of structures can be achieved by the sequential design of experiment (DOE) and the sensitivity analysis. We conducted the DOE with an orthogonal array and the sensitivity analysis of design variables to determine sensitive variables used for connectivity between elements. The modified topology optimization method has advantages such as freedom from penalizing intermediate values and easy application with basic DOE concept.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.73-83
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• 2014

Many recent theoretical developments in the field of machine learning and control have rapidly expanded its relevance to a wide variety of applications. In particular, a variety of portfolio optimization problems have recently been considered as a promising application domain for machine learning and control methods. In highly uncertain and stochastic environments, portfolio optimization can be formulated as optimal decision-making problems, and for these types of problems, approaches based on probabilistic machine learning and control methods are particularly pertinent. In this paper, we consider probabilistic machine learning and control based solutions to a couple of portfolio optimization problems. Simulation results show that these solutions work well when applied to real financial market data.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.03a
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• pp.370-375
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• 2005

This paper describes a systematic way of identifying the horizontal coefficient of consolidation for clayey soil under undrained condition and silty soil under partial drained condition by applying an optimization technique to the early part of dissipation data measured from the self-boring pressuremeter strain holding test. An analytical solution developed by Randolph & Wroth (1979) was implemented in normalized form to express the build-up and dissipation of excess pore pressures around a pressuremeter as a function of the rigidity index. Horizontal coefficient of consolidation was determined by minimizing the differences between theoretical and measured excess pore pressure curves using optimization technique. It was found that the proposed optimization technique can evaluate in-situ horizontal coefficient of consolidation rationally, which is similar with that obtained from the piezocone dissipation test. Furthermore, proposed method can evaluate appropriate coefficient of consolidation for soil under partially drained condition.

• Structural Engineering and Mechanics
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• v.51 no.2
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• pp.229-248
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• 2014

In this paper, the development of a new optimization software for finite element model updating of engineering structures titled as FemUP is described. The program is used for computational FEM model updating of structures depending on modal testing results. This paper deals with the FE model updating procedure carried out in FemUP. The theoretical exposition on FE model updating and optimization techniques is presented. The related issues including the objective function, constraint function, different residuals and possible parameters for FE model updating are investigated. The issues of updating process adopted in FemUP are discussed. The ideas of optimization to be used in FE model updating application are explained. The algorithm of Sequential Quadratic Programming (SQP) is explored which will be used to solve the optimization problem. The possibilities of the program are demonstrated with a three dimensional steel frame model. As a result of this study, it can be said that SQP algorithm is very effective in model updating procedure.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.233-241
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• 2003

The rolling schedule procedure has been an important part of the Enterprise Resource Planning (ERP) systems. The performance of production planning in an ERP system depends on the selection of the three parameters in rolling schedule procedure: frozen interval, replanning interval, and planning horizon (forecast window). This research investigated, in a theoretical approach, the combined impact of selections of those three parameters. The proven mathematical theorems provided guidance to re-duction of instability (nervousness) and to seek the optimal balance between stability and responsiveness of ERP systems. Further the theorems are extended to incorporate the cost structure.

• Bulletin of the Korean Chemical Society
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• v.10 no.6
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• pp.488-491
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• 1989

Theoretical studies on the proton transfer reaction in a formamide dimer have been done by Ab initio SCF calculation. In this study, we have shown several effects on the potential energy profile of the proton transfer in a formamide dimer, such as the effect of a basis set, the effect of a geometry optimization, and the effect of a distance between proton-donor and proton-acceptor.

• Journal of computational fluids engineering
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• v.13 no.4
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• pp.96-106
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• 2008

We review a series of studies on turbulent skin friction drag reduction in wall-turbulence recently conducted in Japan. First, an identity equation relating the skin friction drag and the Reynolds shearstress (the FIK identity) is introduced. Based on the implication of the FIK identity, a new analytical suboptimal feedback control law requiring the streamwise wall-shear stress only is introduced and direct numerical simulation (DNS) results of turbulent pipe flow with that control is reported. We also introduce DNS of an anisotropic compliant surface and parameter optimization using an evolutionary optimization technique.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.5
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• pp.801-810
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• 2004

The Primal-Dual Interior-Point (PDIP) method is currently one of the fastest emerging topics in optimization. This method has become an effective solution algorithm for large scale nonlinear optimization problems. such as the electric Optimal Power Flow (OPF) and natural gas and electricity OPF. This study describes major theoretical developments of the PDIP method as well as practical issues related to implementation of the method. A simple quadratic problem with linear equality and inequality constraints

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.859-866
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• 2006

This study employed the perturbation method, the Edgeworth series, the reliability optimization, the reliability sensitivity technique and the robust design to present a practical and effective approach for the robust reliability design of vehicle components with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulae of the robust reliability design for vehicle components with arbitrary distribution parameters are obtained. The reliability sensitivity is added to the reliability optimization design model and the robust reliability design is described as a multi-objection optimization. On the condition of known first four moments of original random variables, the respective program can be used to obtain the robust reliability design parameters of vehicle components with arbitrary distribution parameters accurately and quickly.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.187-188
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• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.