• Proceedings of the KIEE Conference
• /
• 2002.07a
• /
• pp.121-123
• /
• 2002

In this paper, we preposed a chaos optimization method to reduce computational effort and enhance optimality of the solution in feeder reconfiguration problem. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and more easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 15 buses and 32 buses distribution systems, and the test results indicate that it is able to determine appropriate switching options for global optimum configuration with less computation.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1996.04a
• /
• pp.519-524
• /
• 1996

This paper describes the application of Genetic Algorithms(GAs) to nonlinear constrained mixed optimization problems. Genetic Algorithms are combinatorial in nature, and therefore are computationally suitable for treating discrete and integer design variables. But, several problems that conventional GAs are ill defined are applicaiton of penalty function that can be adapted to transform a constrained optimization problem into an unconstrained 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 Institute of Control, Robotics and Systems
• /
• v.8 no.6
• /
• pp.514-523
• /
• 2002

Feeder arrangement is an important element of process planning for printed circuit board assembly systems. This paper newly proposes a feeder arrangement method for multihead-gantry chip mounters. The multihead-gantry chip mounters are very popular in printed circuit board assembly system, but the research has been mainly focused on single-head-gantry chip mounters. We present an integer programming formulation for optimization problem of multihead-gantry chip mounters, and propose a heuristic method to solve the large NP-complete problem in reasonable time. Dynamic programming method is then applied to feeder arrangement optimization to reduce the overall assembly time. Comparative simulation results are finally presented to verify the usefulness of the proposed method.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.15 no.26
• /
• pp.67-76
• /
• 1992

변수의 어떤 값들에 대해 도함수를 가질 수 없는 함수를 최적화해야 하는 등. OR 에서는 여러 상황이 존재한다. 이것은 Convex Analysis〔12〕서 이론적인 differential calculus를 근저로 하는 Non-differentiable Optimization 또는 Non-smooth Optimization 을 취급하는 것이 된다. 이러한 종류의 미분이 가능하지 않은 최적화문제는 연속함수를 위한 종래의 최적화법으로는 그 해법자체가 갖고 있는 연속성의 한계를 극복할 수 없다. 따라서, 이러한 문제를 해결하기 위해 Demyanov〔4〕가 제시한 quasi-differental function의 정의와 이들 함수에 따른 몇가지 주요정리들을 언급하고, 그것들을 토대로 Non-differentiable optimization problem의 수치적인 방법을 수행하기 위해 일종의 modified gradient 법을 제시한다. 이를 이용해서 numerical experiment를 위한 방법을 구체화하여, unrestricted non-differentable optimization problem에 적응하여, 그 수치해 결과를 보여서 그 타당성음 검토하였다.

• Journal of the Optical Society of Korea
• /
• v.13 no.2
• /
• pp.286-293
• /
• 2009

In this paper, we present an optimal shape design method for a dielectric microlens which is used to focus an incoming infrared plane wave in wideband, by exploiting the finite difference time domain (FDTD) technique and the topology optimization technique. Topology optimization is a scheme to search an optimal shape by adjusting the material properties, which are design variables, within the design space. And by introducing the adjoint variable method, we can effectively calculate a derivative of the objective function with respect to the design variable. To verify the proposed method, a shape design problem of a dielectric microlens is tested when illuminated by a transverse electric (TE)-polarized infrared plane wave. In this problem, the design variable is the dielectric constant within the design space of a dielectric microlens. The design objective is to maximally focus the incoming magnetic field at a specific point in wideband.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2004.05a
• /
• pp.753-758
• /
• 2004

This study is to suggest a probabilistic design determining configurations of slider air bearings with the dimensional manufacturing tolerances of the ABS. The probabilistic design problem is formulated to minimize the variation in flying height from a target value while satisfying the desired probabilities keeping the pitch and roll angles within suitable range. The proposed approach first solves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the probabilistic constraints affected by the random variables with a fixed standard deviation in normal distribution. The RBDO results are directly compared with the values of the initial design and the results of the deterministic optimization, respectively. The reliability analyses are performed by the descriptive sampling (DS) to show the effectiveness and accuracy of the proposed approach. It is demonstrated that the proposed RBDO approach can efficiently obtain an optimum solution satisfying all the desired probabilistic constraints.

• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.695-700
• /
• 2008

Artificial neural network (ANN) has been extensively used in areas of nonlinear system modeling, analysis and design applications. Basically, ANN has its distinct capabilities of implementing system identification and/or function approximation using a number of input/output patterns that can be obtained via numerical and/or experimental manners. The paper describes a role of ANN, especially a back-propagation neural network (BPN) in the context of engineering analysis, design and optimization. Fundamental mechanism of BPN is briefly summarized in terms of training procedure and function approximation. The BPN based causality analysis (CA) is further discussed to realize the problem decomposition in the context of multidisciplinary design optimization. Such CA is also applied to quantitatively evaluate the uncoupled or decoupled design matrix in the context of axiomatic design with the independence axiom.

• Proceedings of the KSME Conference
• /
• 2000.11a
• /
• pp.818-823
• /
• 2000

In practical design studies, most of designers solve multidisciplinary problems with complex design structure. These multidisciplinary problems have hundreds of analysis and thousands of variables. The sequence of process to solve these problems affects the speed of total design cycle. Thus it is very important for designer to reorder original design processes to minimize total cost and time. This is accomplished by decomposing large multidisciplinary problem into several multidisciplinary analysis subsystem (MDASS) and processing it in parallel. This paper proposes new strategy for parallel decomposition of multidisciplinary problem to raise design efficiency by using genetic algorithm and shows the relationship between decomposition and multidisciplinary design optimization (MDO) methodology.

• Journal of Electrical Engineering and Technology
• /
• v.5 no.3
• /
• pp.423-430
• /
• 2010

Particle swarm optimization (PSO) algorithm is designed to find a single global optimal point. However, the PSO needs to be modified in order to find multiple optimal points of a multimodal function. These modifications usually divide a swarm of particles into multiple subswarms; in turn, these subswarms try to find their own optimal point, resulting in multiple optimal points. In this work, we present a new PSO algorithm, called coupling PSO to find multiple optimal points of a multimodal function based on coupling particles. In the coupling PSO, each main particle may generate a new particle to form a couple, after which the couple searches its own optimal point using non-stop-moving PSO algorithm. We tested the suggested algorithm and other ones, such as clustering PSO and niche PSO, over three analytic functions. The coupling PSO algorithm was also applied to solve a significant benchmark problem, the TEAM workshop problem 22.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.14 no.8
• /
• pp.695-701
• /
• 2004

This study is to suggest a Probabilistic design determining configurations of slider air bearings with the dimensional manufacturing tolerances of the ABS. The probabilistic design problem is formulated to minimize the variation in flying height from a target value while satisfying the desired probabilities keeping the pitch and roll angles within a suitable range. The proposed approach first selves the deterministic optimization problem. Then, beginning with this solution, the RBDO is continued with the probabilistic constraints affected by the random variables with a fixed standard deviation in normal distribution. The RBDO results are directly compared with the values of the initial design and the results of the deterministic optimization, respectively. The reliability analyses are performed by the descriptive sampling (DS) to show the effectiveness and accuracy of the proposed approach. It is demonstrated that the Proposed RBDO approach can efficiently obtain an optimum solution satisfying all the desired probabilistic constraints.