• 경영과학
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• 제13권1호
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• pp.97-109
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• 1996

Genetic Algorithms have been successfully applied to various problems (for example, engineering design problems with a mix of continuous, integer and discrete design variables) that could not have been readily solved with traditional computational techniques. But, several problems for which conventional Genetic Algorithms are ill defined are premature convergence of solution and application of exterior penalty function. Therefore, we developed an Improved Genetic Algorithms (IGAs) to solve above two problems. As a case study, IGAs is applied to several nonlinear optimization problems and it is proved that this algorithm is very useful and efficient in comparison with traditional methods and conventional Genetic Algorithm.

• 한국국방경영분석학회지
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• 제9권1호
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• pp.69-74
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• 1983

This article presents a deterministic inventory model for situations in which, during the stockout period, a fraction ${\beta}$ of the demand is backordered and the remaining fraction $1-{\beta}$ is lost. By defining a time proportional backorder cost and a fixed penalty cost per unit lost, a convex objective function representing the average annual cost of operating the inventory system is obtained. The optimal operating policy variables are calculated directly. At the extremes ${\beta}\;=\;1$ and ${\beta}\;=\;0$ the model presented reduces to the usual backorders and lost sales case, respectively.

• 전기학회논문지
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• 제57권9호
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• pp.1624-1627
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• 2008

This paper deals with a linear matrix inequality (LMI) approach to the design of a PID controller for an attraction type magnetic levitation system. First, we convert the $H_ {\infty}$ PID controller problem into a static output feedback problem. We then solve the static output problem by using the recently developed penalty function method. Numerical experiments show the effectiveness of the proposed algorithm.

• 한국산업정보학회논문지
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• 제1권1호
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• pp.63-85
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• 1996

This paper describes the applications of genetic algorithm to nonlinear constrained optimization problems. Genetic algorithms are combinatorial in nature, and therefore are computationally suitable for treating continuous and idstrete integer design variables. For several problems , the conventional genetic algorithms are ill-defined , which comes from the application of penalty function , encoding and decoding methods, fitness scaling, and premature convergence of solution. Thus, we develope a hybrid genetic algorithm to resolve these problems and present two examples to demonstrate the effectiveness of the methodology developed in this paper.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.19-26
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• 1998

The isoparametric spline finite strip method for degenerated shells is presented. In the formulation, both the geometry and the displacement field are represented by uniform cubic B-spline curves. Spline shell strip is degenerated stress-resultant shell with 6 dof at each node;and the penalty function method is used to incorporated the six dof,

• 대한조선학회지
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• 제25권3호
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• pp.35-45
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• 1988

This paper presents a sophisticated Sequential Linear Approximation Method(SLAM) to solve nonlinear optimization problem and the performance of this method is compared with those of the Penalty Function Method(SUMT), Tangent Search Method(TSM) and Flexible Tolerance Method(FTM). To improve the convenience and flexibility in using the proposed SLAM, an user oriented design optimization language is developed and the application examples are shown for the optimization of propeller principal dimensions and the optimization of bulk carrier principal particulars.

• 대한조선학회지
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• 제17권4호
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• pp.46-54
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• 1980

The ship structural design problem is formulated as a general nonlinear optimization problem with constraints. Characteristics of the general structural problems and various optimization techniques are discussed, with special emphasis on penalty function method for constrained problems. A simple example of the solution of a midship structure design of cargo vessel, which complies with the rules of the Korean Register of Shipping is shown using SUMT-exterior method with some search methods.

• 대한전기학회논문지
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• 제32권4호
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• pp.121-127
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• 1983

In this paper an efficient algorithm for Pontriagin's maximum principle is developed. Fletcher-Powell method is adopted as optimization technique which shows fast and stable convergence characteristics. Terminal constraints are alse considered by using Hestens' algorithm and penalty function method together. Control variable inequality constraints are also considered by using Gradient Projection technique combined with Flectcher-Powell method. Test experiment shows good and reliable results.

• Structural Engineering and Mechanics
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• 제3권1호
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• pp.35-48
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• 1995

This paper presents new frequency results for elliptical and semi-elliptical Mindlin plates of various aspect ratios, thicknesses and boundary conditions. The results were obtained using the recently developed computerized Rayleigh-Ritz method for thick plate analysis. For simply supported elliptical plates, it is proposed that the penalty function method be used to enforce the condition of zero rotation of the midplane normal in the tangent plane to the plate boundary.

• 대한의용생체공학회:의공학회지
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• 제36권5호
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• pp.211-220
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• 2015

Recently, model-based iterative reconstruction (MBIR) has played an important role in transmission tomography by significantly improving the quality of reconstructed images for low-dose scans. MBIR is based on the penalized-likelihood (PL) approach, where the penalty term (also known as the regularizer) stabilizes the unstable likelihood term, thereby suppressing the noise. In this work we further improve MBIR by using a more expressive regularizer which can restore the underlying image more accurately. Here we used a spline regularizer derived from a linear combination of the two-dimensional splines with first- and second-order spatial derivatives and applied it to a non-quadratic convex penalty function. To derive a PL algorithm with the spline regularizer, we used a separable paraboloidal surrogates algorithm for convex optimization. The experimental results demonstrate that our regularization method improves reconstruction accuracy in terms of both regional percentage error and contrast recovery coefficient by restoring smooth edges as well as sharp edges more accurately.