• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.151-166
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• 2018

This paper compares the four selections of performance used in the application of genetic algorithms (GAs) to automatically optimize multispectral pixel cluster for unsupervised classification from KOMPSAT-3 data, since the selection among three main types of operators including crossover and mutation is the driving force to determine the overall operations in the clustering GAs. Experimental results demonstrate that the tournament selection obtains a better performance than the other selections, especially for both the number of generation and the convergence rate. However, it is computationally more expensive than the elitism selection with the slowest convergence rate in the comparison, which has less probability of getting optimum cluster centers than the other selections. Both the ranked-based selection and the proportional roulette wheel selection show similar performance in the average Euclidean distance using the pixel clustering, even the ranked-based is computationally much more expensive than the proportional roulette. With respect to finding global optimum, the tournament selection has higher potential to reach the global optimum prior to the ranked-based selection which spends a lot of computational time in fitness smoothing. The tournament selection-based clustering GA is used to successfully classify the KOMPSAT-3 multispectral data achieving the sufficient the matic accuracy assessment (namely, the achieved Kappa coefficient value of 0.923).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.203-211
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• 1999

This paper presents a new approach on genetic on genetic algorithm to economic dispatch problem for valve point discontinuities. Proposed approach in this paper on genetic algorithms improves the performance to solve economic dispatch problem for valve point discontivuities through improved death penalty method, generation-apart elitism, atavism and sexual selection with sexual distinction. Numerical results on a test system consisting of 13 thermal units show that the proposed approach is faster, more robust and powerful than conventional genetic algorithms.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.651-652
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• 2008

In this paper, we suggest a new multiobjective optimization algorithm which is based on the simulated annealing(SA) method. The proposed algorithm uses population-based simulated annealing and adapts elitism in the process of selection.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.7
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• pp.324-332
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• 2001

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Static VAR Compensator(SVC) using a Real Variable Elitism Genetic Algorithm(RVEGA). A SVC, one of the Flexible AC Transmission System(FACTS), constructed by a fixed capacitor(FC) and a thyristor controlled reactor(TCR), is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage. The proposed PSS parameters are optimized using RVEGA in order to maintain optimal operation of generator under the various operating conditions. To decrease the computational time, real variable string is adopted. To verify the robustness of the proposed method, we considered the dynamic response of generator speed deviation and generator terminal voltage by applying a power fluctuation and three-phase fault at heavy load, normal load and light load. Thus, we prove the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system.

• 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.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.739-748
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• 2007

The objective of this research study is to develop the permutation-based genetic algorithm for solving the resource-constrained project scheduling problem in construction engineering by incorporating elitism into genetic algorithm. A key aspect of the algorithm was the development of the elitist roulette selection operator to preserve the best individual solution for the next generation so the improved solution can be obtained. Another notable characteristic is the application of the parallel schedule generation scheme to generate a feasible solution to the problem. Case studies with a standard test problem were presented to demonstrate the performance and accuracy of the algorithm. The computational results indicate that the proposed algorithm produces reasonably good solutions for the resource-constrained project scheduling problem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.6
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1382-1387
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• 1999

This paper presents an optimal fuzzy power system stabilizer to damp out low frequency oscillation. So far fuzzy controllers have been applied to power system stabilizing controllers due to its excellent properties on the nonlinear systems. But the design process of fuzzy logic power system stabilizer requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This paper presents and optimal design method of the fuzzy logic stabilizer using the genetic algorithm. Non-symmetric membership functions are optimally tuned over an evaluation function. The present inputs of fuzzy stabilizer are torque angle error and the change of torque angle error without loss of generality. The coding method used in this paper is concatenated binary mapping. Each linguistic fuzzy variable, defined as the peak of a membership function, is assigned by the mapping from a minimum value to a maximum value using eight bits. The tournament selection and the elitism are used to keep the worthy individuals in the next generation. The proposed system is applied to the one-machine infinite-bus model of a power system, and the results showed a promising possibility.