• Proceedings of the KSME Conference
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• 2007.05a
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• pp.560-565
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• 2007

Motivated by needs such as those in the aerospace industry, this paper demonstrates ability to significantly increase buckling loads of perforated composite laminated plates by synergizing FEM and a genetic optimization algorithm (GA). Plate geometry is discretized into specially-developed 3D degenerated eight-node shell isoparametric layered composite elements. General shell theory, involving incremental nonlinear finite element equilibrium equation, is employed. Fiber orientation within individual plies of each element is controlled independently by the genetic algorithm. Eigen buckling analysis is performed using the subspace iteration method. Available results demonstrate the approach is superior to more conventional methodologies such as modifying ply thickness or the stacking sequence of individual rectilinear plies having common fiber orientation through the plate.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.1
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• pp.19-33
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• 2008

In the previous double auction research for the market optimization, two basic assumptions are usually applied - (1) each trader has a linear or quasi-linear utility function of price and quantity, and (2) buyers as well as sellers have identical utility functions. However, in practice, each buyer and seller in a double auction market may have diverse utility functions for trading goods. Therefore, a flexible and integrated double auction mechanism that can integrate all traders' diverse utility functions is necessary. In particular, the flexible mechanism is more useful in a synchronous double auction because traders can properly change utilities in each round. Therefore, in this paper, we propose a flexible synchronous double auction mechanism in which traders can express diverse utility functions for the price and quantity of the goods, and optimal total market utility is guaranteed. In order to optimize the total market utility which consists of multiple complex utility functions of traders. We show the viability of the proposed mechanism through a several simulation experiments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.683-691
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• 1999

In this paper, it is suggested that the selection method of optimal parameter of power system stabilizer(PSS) with robustness in low frequency oscillation for power system using Real Variable Elitism Genetc Algorithm(RVEGA). The optimal parameters were selected in the case of power system stabilizer with one lead compensator, and two lead compensator. Also, the frequency responses characteristic of PSS, the system eigenvalues criterion and the dynamic characteristic were considered in the normal load and the heavy load, which proved usefulness of RVEGA compare with Yu's compensator design theory.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.853-855
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• 1999

The induction machine has been used frequently for the system that needs static speed because of its simplicity, durability, credibility and efficiency. But it is nonlinear system for its multi-variable interference. Its controller is more complicated than DC machine's one. So vector control method is needed for its high Performance control. This paper shows that vector control algorithm could be more fast and stable by using Genetic algorithm (GA) based upon Darwin's evolution theory and Mendel's genetics. Methods proposed in here are used to design induction machine's vector controller and to use GA for optimizing the controller's parameter. SIMULINK of MATLAB is used for analysis and conviction of control property

• Proceedings of the Korean Society For Composite Materials Conference
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• 2002.10a
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• pp.276-279
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• 2002

A problem formulation and solution for design optimization of laminated composite channel section beam is presented in this study. The objective of this study is the determination of optimum section dimensions of composite laminated channel section beam which has equivalent flexural rigidities to flexural rigidities of steel channel section beam. The analytical model is based on the laminate theory and accounts for the material coupling for arbitrary laminate stacking sequence configuration. The model is used to determine the optimal section dimensions of composite channel section beam. The web height, flange width and thickness of the beam are treated as design variables. The solutions described are found using a global search algorithm, Genetic Algorithms (GA).

• Structural Engineering and Mechanics
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• v.52 no.4
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• pp.815-827
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• 2014

Buckling optimization of laminated composite plates is significant as they fail because of buckling under in-plane compressive loading. The plate is usually modeled without cutout so that the buckling strength is found analytically using classical laminate plate theory (CLPT). However in real world applications, the composite plates are modeled with cutouts for getting them assembled and to offer the provisions like windows, doors and control system. Finite element analysis (FEA) is used to analyze the buckling strength of the plate with cutouts and it leads to high computational cost when the plate is optimized. In this article, a genetic algorithm based optimization technique is used to optimize the composite plate with cutout. The computational time is highly reduced by replacing FEA with artificial neural network (ANN). The effectiveness of the proposed method is explored with two numerical examples.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.8
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• pp.1119-1126
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• 1995

The construction of rule-base for a nonlinear time-varying system, becomes much more complicated because of model uncertainty and parameter variations. Furthemore, FLC does not have an ability of adjusting rule- base in responding to some sudden changes of control environments. To cope with these problems, an auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), which is known to be very effective in the optimization problem, will be proposed. The tuning of the proposed system is performed by two tuning processes(the course tuning process and the fine tuning/adaptive learning process). The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.8
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• pp.1211-1224
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• 2004

Two round jets. impinged and pulsed. were measured with high-resolution 3D-PTV technique. The measurement system consists of three CCD cameras, Ar-ion laser, an image grabber and a host computer. Two fitness functions were introduced in a genetic algorithm in order to enhance the correspondences of the particles. One was based on a concept of the continuum theory and the other one was based on a minimum distance error. The velocity profiles of the impinged jet obtained by the constructed 3D-PTV system were compared with those of LDV measurements made in this study. The head vortex of the jet was visualized by LIF and was reconstructed by the constructed high-resolution 3D-PTV system for comparisons.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.1-7
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• 2012

A Failure data from operating condition includes various failures. Reliability evaluation by operating condition is more correct than test condition. Additional, the evaluation result by operating condition is widely used for quality assurance, forecasting amount of manufacturing at EOL. To discover valuable things from the failure data, arrangement of the failure data and information technique to handle data is needed among many failure data. This paper introduces a reliability prediction program to solve this problem based on the failure. And new technologies for parameters estimation with method of Graphic-Wizard-Parameters-Estimation and Genetic Algorithm are introduced.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.119-125
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• 2011

The part family (PF) formation in a cellular manufacturing has been a key issue for the successful implementation of Group Technology (GT). Basically, a part has two different attributes; i.e., design and manufacturing. The respective similarity in both attributes is often conflicting each other. However, the two attributes should be taken into account appropriately in order for the PF to maximize the benefits of the GT implementation. This paper proposes a clustering algorithm which considers the two attributes simultaneously based on pareto optimal theory. The similarity in each attribute can be represented as two individual objective functions. Then, the resulting two objective functions are properly combined into a pareto fitness function which assigns a single fitness value to each solution based on the two objective functions. A GA is used to find the pareto optimal set of solutions based on the fitness function. A set of hypothetical parts are grouped using the proposed system. The results show that the proposed system is very promising in clustering with multiple objectives.