• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.5
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• pp.489-495
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• 2014

A micro-genetic algorithm (MGA) is one of the improved forms of a genetic algorithm. It is used to reduce the number of iterations and the computing resources required by using small populations. The efficiency of MGAs has been proved through many problems, especially problems with 3-5 design variables. This study proposes an optimization algorithm based on the sequential design of experiments (SDOE) and an MGA. In a previous study, the authors used the SDOE technique to reduce trial-and-error in the conventional approximate optimization method by using the statistical design of experiments (DOE) and response surface method (RSM) systematically. The proposed algorithm has been applied to various mathematical examples and a structural problem.

• Journal of Korean Society of Steel Construction
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• v.17 no.2 s.75
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• pp.173-181
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• 2005

This study deals with a method to identify damages of free vibrating thin plate structures using the combined finite element method (FEM) and the advanced uniform micro-genetic algorithm.To solve the inverse problem using the combined method, this study uses several natural frequencies instead of mode shapes in a structure as the measured data. The technique described in this paper allows us not only to detect the damaged elements but also to find their numbers, locations, and the extent of damage.To demonstrate the feasibility of the proposed method, the algorithm is applied to a free vibrating steel thin plate structures with arbitrary damages. From the standpoint of computation efficiency, the proposed method in this study has advantages when compared with the existing simple genetic algorithms. The numerical examples demonstrate that the method using micro-genetic algorithms can possibly detect correctly the damages of thin plates from only several natural frequencies instead of their natural modes.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.1
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• pp.79-87
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• 2017

The microphysical processes of the numerical weather prediction (NWP) model cover the following : fall speed, accretion, autoconversion, droplet size distribution, etc. However, the microphysical processes and parameters have a significant degree of uncertainty. Parameter estimation was generally used to reduce errors in NWP models associated with uncertainty. In this study, the micro- genetic algorithm and harmony search algorithm were used as an optimization algorithm for estimating parameters. And we estimate parameters of microphysics for the Unified model in the case of precipitation in Korea. The differences which occurred during the optimization process were due to different characteristics of the two algorithms. The micro-genetic algorithm converged to about 1.033 after 440 times. The harmony search algorithm converged to about 1.031 after 60 times. It shows that the harmony search algorithm estimated optimal parameters more quickly than the micro-genetic algorithm. Therefore, if you need to search for the optimal parameter within a faster time in the NWP model optimization problem with large calculation cost, the harmony search algorithm is more suitable.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.52.1-52.1
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• 2005

• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.4
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• pp.169-178
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• 2010

In this study, the optimal strengthening by micro genetic algorithm(${\mu}$-GA) method is proposed for improvement of load-carrying capacity of RC hollow slab bridges using external prestressing. The Qeen-post type and King-post type are considered for the optimal strengthening. The type for optimal strengthening, deviator, areas of tendons and the number of anchor are calculated by ${\mu}$-GA. The objective function is constituted with dimensionless cost of tendon and steel for optimal strengthening. The constraints are formulated by design specification for bridges and anchors. The validity of this study is presented by analysis of the results after the optimal strengthening of the RC hollow slab bridge.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.4
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• pp.54-64
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• 2005

The study investigated genetic algorithms for the optimal control model of maximum height vertical jumping. The model includes forward dynamic simulations by the neural excitation-control variables. Convergence of genetic algorithms is very slow. In this paper the micro genetic algorithm(micro-GA) was used to reduce the computation time. Then a near optimal solution from micro-GA was an initial solution for VF02, which is one of well-developed and proven nonlinear programming algorithms. This approach provided the successful optimal solution for maximum-height jumping without a reasonable initial guess.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.1-8
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• 2016

The Korea Meteorological Administration has operated the Automatic Weather Stations, of the average 13 km horizontal resolution, to observe rainfall. However, an additional RADAR network also has been operated in all-weather conditions, because AWS network could not observed rainfall over the sea. In general, the rain rate is obtained by estimating the relationship between the radar reflectivity (Z) and the rainfall (R). But this empirical relationship needs to be optimized on the rainfall over the Korean peninsula. This study was carried out to optimize the Z-R relationship in the summer of 2014 using a parallel Micro Genetic Algorithm. The optimized Z-R relationship, $Z=120R^{1.56}$, using a micro genetic algorithm was different from the various Z-R relationships that have been previously used. However, the landscape of the fitness function found in this study looked like a flat plateau. So there was a limit to the fine estimation including the complex development and decay processes of precipitation between the ground and an altitude of 1.5km.

• Journal of Korean Society of Steel Construction
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• v.23 no.4
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• pp.465-474
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• 2011

In this study, a microgenetic algorithm was used to find the optimum cross-section and shape of dome structures. The allowable stress and Euler buckling stress were considered constraints when the weight of the trusses was minimum. The design optimization of the truss structures involved arriving at the optimum sizes of the cross-section and geometric coordinate. The features of the proposed method, which helped in the modeling of and application to the optimal design of truss structures, were demonstrated using the microgenetic algorithm, by solving sample problems.

• Journal of Korean Society of Steel Construction
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• v.24 no.5
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• pp.549-558
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• 2012

This study identifies the damage detection of truss structures by using genetic algorithm(GA) from changed elements properties. To model the damaged truss structures, the modulus of elasticity of some specific elements is reduced. The analysis of truss structures is performed with static analysis by applying uniform load, and the location and extent of structural damage is detected by comparing the stain of each element of healthy truss structures with damaged truss structures using genetic algorithm. In this study, some numerical examples are presented to detect the location and extent of damage using genetic algorithm.

• Proceedings of the KWS Conference
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• 2007.11a
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• pp.57-59
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• 2007