• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.15 no.2
• /
• pp.255-262
• /
• 2015

In the absence of a deterministic algorithm for economic load dispatch optimization problem (ELDOP), existing algorithms proposed as solutions are inevitably non-deterministic heuristic algorithms. This paper, therefore, proposes a balance-and-swap algorithm to solve an ELDOP. Firstly, it balances the initial value to ${\Sigma}P_i=P_d$ by subsequently reducing power generation for each adult-step and baby-step and selects the minimum cost-generating method. Subsequently, it selects afresh the minimum cost-generating method after an optimization of the previously selected value with adult-step baby-step swap and giant-step swap methods. Finally, we perform the $P_i{\pm}{\beta}$, (${\beta}=0.1,0.01,0.001,0.0001$) swap. When applied to the 3 most prevalently used economic load dispatch problem data, the proposed algorithm has obtained improved results for two and a result identical to the existing one for the rest. This algorithm thus could be applied to ELDOP for it has proven to consistently yield identical results and to be applicable to all types of data.

• Journal of the Korean Society for Aviation and Aeronautics
• /
• v.31 no.2
• /
• pp.55-65
• /
• 2023

Due to extreme urbanization, ground transportation in the city center is saturated, and problems such as the lack of expansion infrastructure and traffic congestion increase social costs. To solve this problem, a 3D mobility platform, Urban Air Mobility (UAM), has emerged as a new alternative. A vertiport is a physical space that conducts a similar role to an airport terminal. Vertiport consists of take-off and landing facilities (TLOF, Touchdown and Lift-Off area), space for boarding and disembarking from UAM aircraft (gates), taxiways, and passenger terminals. The type of vertiport (structure, number of facilities) and concept of operations are key variables that determine the number of UAM aircraft that can be accommodated per hour. In this study, a capacity calculation method was presented using an optimization technique (Deterministic Integer Linear Programming). The absolute capacity of the vertiport was calculated using an optimization technique, and a sensitivity analysis was also performed.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.27 no.7
• /
• pp.1234-1242
• /
• 2003

In this paper we present a simple and efficient robust optimal design formulation for MEMS structures and its application to a resonant-type micro probe. The basic idea is to use the gradient index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-effective and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation. This method, although shown for MEMS structures, may as well be easily applied to conventional mechanical structures where information on uncertainties is lacking but robustness is highly important.

• International Journal of Automotive Technology
• /
• v.4 no.4
• /
• pp.193-201
• /
• 2003

The problem of brake judder is typically caused by defects of quality manufacturing. DFSS (Design for six sigma) is a design process for quality improvement. DFSS will result in more improved but less expensive quality products. This paper presents an implementation of DFSS for quality improvement of the brake judder of heavy-duty trucks. Carrying out 5 steps of DFSS, the major reasons for defects of quality are found. The numerical approximation of the brake system is derived by means of the response surface method. Its quality for brake judder is improved by using the sigma based robust design methodology. Results are compared between the conventional deterministic optimal design and the proposed sigma based robust design. The proposed one shows that manufacturing cost may increase as the quality level increase. The proposed one, however, is more economical in aspect of the overall cost since the probability of failure dramatically goes down.

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1846-1851
• /
• 2003

Approximate optimization has become popular in engineering field such as MDO and Crash analysis which is time consuming. To accomplish efficient approximate optimization, accuracy of approximate model is very important. As surrogate model, Kriging have been widely used approximating highly nonlinear system . Because Kriging employs interpolation method, it is adequate for deterministic computer simulation. Because there are no random errors and measurement errors in deterministic computer simulation, instead of classical DOE ,space filling experiment design which fills uniformly design space should be applied. In this work, various space filling designs such as maximin distance design, maximum entropy design are reviewed. And new design improving maximum entropy design is suggested and compared.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.29 no.1 s.232
• /
• pp.59-66
• /
• 2005

In this paper, a robust stationary Kalman filter is designed by minimizing selected performance indices so that it is less sensitive to uncertainties. The uncertainties include not only stochastic factors such as process noise and measurement noise, but also deterministic factors such as unknown initial estimation error, modeling error and sensing bias. To reduce the effect on the uncertainties, three performance indices that should be minimized are selected based on the quantitative error analysis to both the deterministic and the stochastic uncertainties. The selected indices are the size of the observer gain, the condition number of the observer matrix, and the estimation error variance. The observer gain is obtained by optimally solving the multi-objectives optimization problem that minimizes the indices. The robustness of the proposed filter is demonstrated through the comparison with the standard Kalman filter.

• International Journal of Aeronautical and Space Sciences
• /
• v.18 no.4
• /
• pp.780-787
• /
• 2017

The propellant grain configuration is a design variable that determines the shape and performance of a solid rocket motor. Grain configuration variables have complicated effects on the motor performance; so the global optimization problem has to be solved in order to design the configuration variables. The grain performance has been analyzed by means of the grain burn-back and internal ballistic analysis, and the optimization technique searches for the configuration variables that satisfy the requirements. The deterministic and stochastic optimization techniques have been applied for the grain optimization, but the results are imperfect. In this study, the optimization design of the configuration variables has been performed using the hybrid optimization technique, which combines those two techniques. As a result, the hybrid optimization technique has proved to be efficient for the grain optimization design.

• Journal of Korean Society of Steel Construction
• /
• v.16 no.6 s.73
• /
• pp.819-832
• /
• 2004

This study describes an efficient and facile method for configuration optimum design of structures. One of the ways to achieve numerical shape representation and the selection of design variables is using the design element concept. Using this technique, the number of design variables could be drastically reduced. Isoparametric mapping was utilized to automatically generate the finite element mesh during the optimization process, and this made it possible to easily calculate the derivatives of the coordinates of generated finite element nodes w.r.t. the design variables. For the structural analysis, finite element analysis was adopted in the optimization procedure, and two different techniques(the deterministic method, a modified method of feasible direction; and the stochastic method, a genetic algorithms) were applied to obtain the minimum volumes and section areas for an efficient configuration optimization procedure. Futhermore, spline interpolation was introduced to present a realistic optimum configuration that meet the manufacturing requirements. According to the results of several numerical examples(steel structures), the two techniques suggested in this study simplified the process of configuration optimum design of structures, and yielded improved objective function values with a robust convergence rate. This study's applicability and capability have therefore been demonstrated.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.28 no.5
• /
• pp.503-510
• /
• 2004

In this paper, the well-conditioned observer for a stochastic system is designed so that the observer is less sensitive to the ill-conditioning factors in transient and steady-state observer performance. These factors include not only deterministic uncertainties such as unknown initial estimation error, round-off error, modeling error and sensing bias, but also stochastic uncertainties such as disturbance and sensor noise. In deterministic perspectives, a small value in the L$_{2}$ norm condition number of the observer eigenvector matrix guarantees robust estimation performance to the deterministic uncertainties. In stochastic viewpoints, the estimation variance represents the robustness to the stochastic uncertainties and its upper bound can be minimized by reducing the observer gain and increasing the decay rate. Both deterministic and stochastic issues are considered as a weighted sum with a LMI (Linear Matrix Inequality) formulation. The gain in the well-conditioned observer is optimally chosen by the optimization technique. Simulation examples are given to evaluate the estimation performance of the proposed observer.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.7 no.3
• /
• pp.3-11
• /
• 2008

Robust design pioneered by Dr. G. Taguchi has been applied to versatile engineering problems for improving quality. Since 1980s, the Taguchi method has been introduced to numerical optimization, complementing the deficiencies of deterministic optimization, which is often called the robust optimization. In this study, the robust optimization strategy is proposed by considering the robustness of objective and constraint functions. The statistics of responses in the functions are surrogated by kriging models. In addition, objective and/or constraint function is represented by the probability of success, thus facilitating robust optimization. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.