• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.157-160
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• 2000

This paper deals with the fuzzy modeling for the complex and uncertain system in which conventional and mathematical models may fail to give satisfactory results. mGA(messy Genetic Algorithm) has more effective and adaptive structure than sGA with respect to using changeable-length string and VEGA(Virus Evolution Genetic) Algorithm) can search the global and local optimal solution simultaneously with reverse transcription operator and transduction operator. Therefore in this paper, the optimal fuzzy model is obtained using Virus-messy Genetic Algorithm(Virus-mGA). In this method local information is exchanged in population so that population may sustain genetic divergence. To prove the surperioty of the proposed approach, we provide the numerical example.

• 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).

• Journal of applied mathematics & informatics
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• v.27 no.5_6
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• pp.1411-1427
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• 2009

We propose a model based on Lotka-Volterra dynamics with two competing spices which are affected not only by harvesting but also by the presence of a predator, the third species. Hyperbolic and linear response functions are considered. We derive the conditions for global stability of the system using Lyapunov function. The optimal harvest policy is studied and the solution is derived in the interior equilibrium case using Pontryagin's maximal principle. Finally, some numerical examples are discussed. The nature of variations in the two prey species and one predator species is studied extensively through graphical illustrations.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1169-1182
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• 2020

The ant colony optimization (ACO) algorithm is a classical metaheuristic optimization algorithm. However, the conventional ACO was liable to trap in the local minimum and has an inherent slow rate of convergence. In this work, we propose a novel combinatorial ACO algorithm (CG-ACO) to alleviate these limitations. The genetic algorithm and the cloud model were embedded into the ACO to find better initial solutions and the optimal parameters. In the experiment section, we compared CG-ACO with the state-of-the-art methods and discussed the parameter stability of CG-ACO. The experiment results showed that the CG-ACO achieved better performance than ACO_R, simple genetic algorithm (SGA), CQPSO and CAFSA and was more likely to reach the global optimal solution.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.197-199
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• 2001

This paper presents a Tabu Search (TS) based algorithm to solve the Optimal Power Flow (OPF) problem, converses rapidly to global optima by means of escaping local minima. In this paper, a new approach based on the random TS algorithm with continuous variable is proposed to find that a solution to the OPF problem within reasonable time complexity. To verify the efficiency of the proposed approach, case studies are made for IEEE 30-bus system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.8
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• pp.1360-1366
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• 2007

In this paper, the load balancing which is one of the distribution power system's operation purposes was studied. Reconfiguration of Distribution power system presents that the configuration is changed by changing the switch on/off status which exists in the system according to the mentioned purpose. Through this method, the load of distribution power system is shown to be balanced. As a characteristic of complicated distribution power system, system is designed by being applied by OOP(Object Oriented Programming) method which connected more flexibly than existing Procedural Programming method, and the process of calculating the distflow and the loss of configurated system is shown. In addition, this paper suggests more efficient method compared by the results of reconfiguration on the purpose of the loss minimization and by the result of distribution power system reconfiguration on the purpose of load balancing. Moreover, it searches for the method to approach the global optimal solution more quickly.

• Advances in aircraft and spacecraft science
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• v.9 no.5
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• pp.433-447
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• 2022

This work deals with an explicit guidance and control architecture for autonomous lunar ascent and orbit injection, i.e., the locally-flat near-optimal guidance, accompanied by nonlinear reduced-attitude control. This is a new explicit guidance scheme, based on the local projection of the position and velocity variables, in conjunction with the real-time solution of the associated minimum-time problem. A recently-introduced quaternion-based reduced-attitude control algorithm, which enjoys quasi-global stability properties, is employed to drive the longitudinal axis of the ascent vehicle toward the desired direction. Actuation, based on thrust vectoring, is modeled as well. Extensive Monte Carlo simulations prove the effectiveness of the guidance, control, and actuation architecture proposed in this study for precise lunar orbit insertion, in the presence of nonnominal flight conditions.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.173-184
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• 2004

In this paper, we find the approximate solution of a second order nonlinear partial differential equation on a simple connected region in $R^2$. We transfer this problem to a new problem of second order nonlinear partial differential equation on a rectangle. Then, we transformed the later one to an equivalent optimization problem. Then we consider the optimization problem as a distributed parameter system with artificial controls. Finally, by using the theory of measure, we obtain the approximate solution of the original problem. In this paper also the global error in $L_1$ is controlled.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.173-176
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• 1999

This paper shows a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a Polishing robot. Using this method, the number of inference rules and the shape of membership functions are determined by the genetic algorithm. The fuzzy outputs of the consequent part are derived by the gradient descent method. Also, it is guaranteed that .the selected solution become the global optimal solution by optimizing the Akaike's information criterion expressing the quality of the inference rules. It is shown by simulations that the method of fuzzy inference by the genetic algorithm provides better learning capability than the trial and error method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.359-369
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• 1999

The paper describes the study of concurrent subspace optimization(CSSO) for coupled multidisciplinary design optimization (MDO) techniques in mechanical systems. This method is a solution to large scale coupled multidisciplinary system, wherein the original problem is decomposed into a set of smaller, more tractable subproblems. Key elements in CSSO are consisted of global sensitivity equation(GSE), subspace optimization (SSO), optimum sensitivity analysis(OSA), and coordination optimization problem(COP) so as to inquiry valanced design solutions finally, Automatic differentiation has an ability to provide a robust sensitivity solution, and have shown the numerical numerical effectiveness over finite difference schemes wherein the perturbed step size in design variable is required. The present paper will develop the automatic differentiation based concurrent subspace optimization(AD-CSSO) in MDO. An automatic differentiation tool in FORTRAN(ADIFOR) will be employed to evaluate sensitivities. The use of exact function derivatives in GSE, OSA and COP makes Possible to enhance the numerical accuracy during the iterative design process. The paper discusses how much influence on final optimal design compared with traditional all-in-one approach, finite difference based CSSO and AD-CSSO applying coupled design variables.