• Journal of the Korea institute for structural maintenance and inspection
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• v.8 no.3
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• pp.159-167
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• 2004

The objective of this study is development of the optimum design program to minimize the cost for PSC box girder bridge using the full staging method to indicate the necessity for the optimum design applied many types of bridges. It also considered the proper span length to girder depth ratio and the cell number along the width of bridge. This program used SUMT procedure and Kavlie's extended penalty function to allow infeasible design points in the process. Powell's direct method was used in searching design points and Gradient Approximate Method was used to reduce design hours. This study showed the convergence in design parameter and correlation of totally optimized cost according to cell numbers, span lengths, and lane numbers.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.6
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• pp.795-804
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• 2002

The optimal design code of an axial flow pump has been developed to determine geometric and fluid dynamic variables under hydrodynamic as well as mechanical design constraints. The design code includes the optimization of the complete radial distribution of the geometry by determining the coefficients of 2$^{nd}$ order polynomials to represent the three-dimensional geometry. The optimization problem has been formulated with a nonlinear multivariable objective function, maximizing the efficiency and stall margin, while minimizing the net positive suction head required. Calculation of the objective function is based on the mean streamline analysis and through-flow analysis using the present state-of-the-art model. The optimal solution is calculated using the penalty function method in which the genetic optimizer is employed. The optimized efficiency and design variables are presented in this paper as a function of non-dimensional specific speed in the range, 2$\leq$ $n_{s}$ $\leq$10. The results can be used in preliminary design of axial flow pumps.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.15-22
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• 1996

Methods to find an optimal solution that is the function of the design variables satisfying all constraints have been studied, there are still many difficulties to apply them to optimal design problems. A method to solve the above difficulties is developed by using Genetic Algorithms. but, several problems that conventional GAs are ill defined are application of penalty function that can be adapted to transform a constrained 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.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.66-78
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• 2001

This paper deals with problem of determining process target value under automated visual inspection(AVI) system. Three independent error sources - digitizing error, illumination error, and positional error - which have a close relationship with the performance of the AVI system, are considered. Assuming that digitizing error is uniformly or normally distributed and illumination and positional errors are normally distributed, respectively, the distribution function for the error of measured lengths is derived when the length of a product is measured by the AVI system. Then, Optimal target values under two error models of AVI system are obtained by minimizing the total expected cost function which consists of give away, rework and penalty cost. To validate two process setting models, AVI system for drinks filling process is made up and test results are discussed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.2
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• pp.544-556
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• 1991

The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust and efficient. A general-purpose nonlinear optimization program IDOL (Interactive Design Optimization Library) is developed based on the Augmented Lagrange Mulitiplier (ALM) method. The ideas of selecting a good initial design point, using resonable initial values for Lagrange multipliers, constraints scaling, descent vector restarting, and dynamic stopping criterion are employed for computational enhancement to the ALM method. A descent vector is determined by using the Broydon-Fletcher-Goldfarb-Shanno (BFGS) method. For line search, the Incremental-Search method is first used to find bounds on the solution, then the bounds are reduced by the Golden Section method, and finally a cubic polynomial approximation technique is applied to locate the next design point. Seven typical test problems are solved to show IDOL efficient and robust.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.902-907
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• 2004

In this paper, a multi-step optimization using a G.A. (Genetic Algorithm) with variable penalty function is introduced to the structural design optimization of a 5-head route machine. Our design procedure consist of two design optimization stage. The first stage of the design optimization is static design optimization. The following stage is dynamic design optimization stage. In the static optimization stage, the static compliance and weight of the structure are minimized simultaneously under some dimensional constraints and deflection limits. On the other hand, the dynamic compliance and the weight of the machine structure are minimized simultaneously in the dynamic design optimization stage. As the results, dynamic compliance of the 5-head router machine was decreased by about 37％ and the weight of the structure was decreased by 4.48％ respectively compared with the simplified structure model.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.289-291
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• 2000

In a competitive electricity power market, the price of electricity changes instantly, that of conventional market is predetermined and hardly changes. In such a new environment, customers' behaviors change instantly according to the changing electricity prices. If we develop a electricity load model that well describes the behavior of electricity consumers, we can utilize that model in forecasting the amount of future load, solving the load flow problem and finding the weak point of the system. In this paper new electricity model that considers the price of electricity and power factor of the load is presented. While conventional load model, which is demand function of electricity, uses the price of real and reactive power as the independent variable of the demand function. this new load model uses price of real power and penalty factor according to the power factor for the calculation of amount of electricity demand.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.16 no.4
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• pp.36-44
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• 2007

This paper is focused on the optimum design for decreasing volume and increasing reliability of multi-stage gear drive. For the optimization on volume and reliability, multi-objective optimization is used. The genetic algorithm is introduced to multi-objective optimization method and it is used to develop the optimum design program using exterior penalty function method to solve the complicated subject conditions. A 5 staged gear drive(geared motor) is chosen to compare the result of developed optimum design method with the existing design. Each of the volume objective, reliability objective, and volume-reliability multi-objectives are performed and compared with existing design. As a result, optimum solutions are produced, which decrease volume and increase reliability. It is shown that the developed design method is good for multi-stage gear drive design.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.315-318
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• 1995

The optimum design problem of a coat-hanger die is solved by the inverse formulation. The flow in the die is analyzed using three-dimensional model. The new model for the manifold geometry is developed for the inverse formulation. The inverse problem for the optimum die geometry is formed as the optimization problem whose objective function is the linear combination of the square sum of pressure gradient deviation at die exit and the penalty function relating to the measure of non-smoothness of solution. From the several iterative solutions of the optimization problem, the optimum solution can be obtained automatically while producing the uniform flow rate distribution at die exit.