• Journal of Korean Association for Spatial Structures
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• v.4 no.4 s.14
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• pp.91-98
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• 2004

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. This method is an unconstrained optimization technique, so the constraints are handled in an implicit manner. The most popular way of handling constraints is to transform the original constrained problem into an unconstrained problem, using the concept of penalty function. I present the 3 fitness functions which represent the reject strategy, the penalty strategy, and the combined strategy. I make the design program using the 3 fitness Auctions and it is applied to the design problem of a gable frame and a 2 story 3 span frame.

• Journal of Korean Association for Spatial Structures
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• v.19 no.2
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• pp.43-50
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• 2019

A smart connective control system was invented recently for coupling control of adjacent buildings. Previous studies on this topic focused on development of control algorithm for the smart connective control system and design method of control device. Usually, a smart control devices are applied to building structures after structural design. However, because structural characteristics of building structure with control devices changes, a iterative design is required for optimal design. To defeat this problem, an integrated optimal design method for a smart connective control system and connected buildings was proposed. For this purpose, an artificial seismic load was generated for control performance evaluation of the smart coupling control system. 20-story and 12-story adjacent buildings were used as example structures and an MR (magnetorheological) damper was used as a smart control device to connect adjacent two buildings. NSGA-II was used for multi-objective integrated optimization of structure-smart control device. Numerical simulation results show the integrated optimal design method proposed in this study can provide various optimal designs for smart connective control system and connected buildings presenting good control performance.

• Journal of Korean Association for Spatial Structures
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• v.21 no.4
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• pp.49-56
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• 2021

This study aims to develop a form-finding algorithm for a single-layered pneumatic membrane. The initial shape of this pneumatic membrane, which is an air-supported type pneumatic membrane, is to find a state in which a given initial tension and internal pneumatic pressure are in equilibrium. The algorithm developed to satisfy these conditions is that a nonlinear optimization problem based on the force method considering the deformed shape is formulated, and, it's able to find the shape by iteratively repeating the process of obtaining a solution of the governing equations. An computational technique based on the Gauss-Newton method was used as a method for obtaining solutions of nonlinear equations. In order to verify the validity of the proposed form-finding algorithm, a single-curvature pneumatic membrane example and a double-curvature air pneumatic membrane example were adopted, respectively. In the results of these examples, it was possible to well observe the step-by-step convergence process of the shape of the pneumatic membrane, and it was also possible to confirm the change in shape according to the air pressure. In addition, the calculation results of the shape and internal force after deformation due to initial tension, air pressure, and self-weight were obtained.

• Journal of Korean Association for Spatial Structures
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• v.8 no.4
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• pp.47-55
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• 2008

This paper deals with basic theories and some numerical results on structural optimization for geodesic dome. First of all, the space efficiency of geodesic dome is investigated by using the ratio of icosahedron's surface area to the internal volume enclosed by it. The procedure how to create the geodesic dome is also provided in systematic way and implemented and utilized into the design optimization code ISADO-OPT. The mathematical programming technique is introduced to find out the optimum pattern of member size of geodesic dome against a point load. In this study, total weight of structure is considered as the objective function to be minimized and the displacement occurred at loading point and member stresses of geodesic dome are used as the constraint functions. The finite difference method is used to calculate the design sensitivity of objective function with respect to design variables. The SLP, SQP and MFDM available in the optimizer DoT is used to search optimum member size patterns of geodesic dome. It is found to be that the optimum member size pattern can be efficiently obtained by using the proposed design optimization technique and numerical results can be used as benchmark test as a basic reference solution for design optimization of dome structures.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.537-542
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• 2001

In recent engineering, the designer has become more and more dependent on computer simulation. But defining exact model using computer simulation is too expensive and time consuming in the complicate systems. Thus, designers often use approximation models, which express the relation between design variables and response variables. These models are called metamodel. In this paper, we introduce one of the metamodel, named Kriging. This model employs an interpolation scheme and is developed in the fields of spatial statistics and geostatistics. This class of interpolating model has flexibility to model response data with multiple local extreme. By reason of this multi modality, we can't use any gradient-based optimization algorithm to find global extreme value of this model. Thus we have to introduce global optimization algorithm. To do this, we introduce DE(Differential Evolution). DE algorithm is developed by Ken Price and Rainer Storn, and it has recently proven to be an efficient method for optimizing real-valued multi-modal objective functions. This algorithm is similar to GA(Genetic Algorithm) in populating points, crossing over, and mutating. But it introduces vector concept in populating process. So it is very simple and easy to use. Finally, we show how we determine Kriging metamodel and find global extreme value through two mathematical examples.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.4
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• pp.398-405
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• 2016

A shape of loop-pipe in a compressor affects the vibration of compressor. In this paper, optimal design of shape of loop-pipe to decrease the stress was carried out. Body and shell were assumed to be rigid, while loop-pipe is considered to be flexible. The finite element model was derived and programmed. Genetic algorithm was used for optimization. Locations of 18 point in loop-pipe were considered as shape variables, while the shapes of loop-pipe were interpolated as polynomials or ellipses. Maximum stress of loop-pipe was used as a fitness function for optimization. The spatial constraints and acceleration response of shell were also considered in optimization. The maximum stress and acceleration could be reduced by 79 % and 49 % respectively.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.

• Journal of the Korean Society of Safety
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• v.39 no.1
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• pp.96-103
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• 2024

The demand for mass calculation of offsite consequence analysis to conduct exhaustive single-unit or multi-unit Level 3 PSA is increasing. In order to perform efficient offsite consequence analyses, the Korea Atomic Energy Research Institute is conducting model optimization studies to minimize the analysis time while maintaining the accuracy of the results. A previous study developed a model optimization method using efficient plume segmentation and verified its effectiveness. In this study, we investigated the possibility of optimizing the model through particle size distribution setting by checking the reduction in analysis time and deviation of the results. Our findings indicate that particle size distribution setting affects the results, but its effect on analysis time is insignificant. Therefore, it is advantageous to set the particle size distribution as fine as possible. Furthermore, we evaluated the effect of multithreading and confirmed its efficiency. Future optimization studies should be conducted on various input factors of offsite consequence analysis, such as spatial grid settings.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.199-203
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• 2016

A brain-computer interface or BCI provides an alternative method for acting on the world. Brain signals can be recorded from the electrical activity along the scalp using an electrode cap. By analyzing the EEG, it is possible to determine whether a person is thinking about his/her hand or foot movement and this information can be transferred to a machine and then translated into commands. However, we do not know which information relates to motor imagery and which channel is good for extracting features. A general approach is to use all electronic channels to analyze the EEG signals, but this causes many problems, such as overfitting and problems removing noisy and artificial signals. To overcome these problems, in this paper we used a new optimization method called the Fruit Fly optimization algorithm (FOA) to select the best channels and then combine them with CSP method to extract features to improve the classification accuracy by linear discriminant analysis. We also used particle swarm optimization (PSO) and a genetic algorithm (GA) to select the optimal EEG channel and compared the performance with that of the FOA algorithm. The results show that for some subjects, the FOA algorithm is a better method for selecting the optimal EEG channel in a short time.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.1-8
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• 2007

In this paper, research on joint optimization of the image spatial registration and the exposure compensation is conducted. The exposure compensation is performed in a frame work of the intensity compensation based on the polynomial approximation of the relationship between images. This compensation is jointly combined with the registration problem employing the Gauss-Newton nonlinear optimization method. In this paper, to perform for a simple and stable optimization, the block-coordinate method is combined with the Gauss-Newton optimization and extensively compared with the traditional approaches. Furthermore, regression analysis is considered in the compensation part for a better stable performance. By combining the block-coordinate method with the Gauss-Newton optimization, we can obtain a compatible performance reducing the computational complexity and stabilizing the performance. In the numerical result for a particular image, we obtain a satisfactory result for 10 repeats of the iteration, which implies a 50% reduction of the computational complexity. The error is also further reduced by 1.5dB compared to the ordinary method.